Deck 13: Analysis of Variance

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Question
The between-treatments variance is based on a weighted sum of squared differences between the ________.

A) population variances and the overall mean of the data set
B) sample means and the overall mean of the data set
C) sample variances and the overall mean of the data set
D) population means and the overall mean of the data set
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Question
Which of the following is the correct interpretation of Fisher's 100(1 − α)% confidence interval for μi - μj?

A) If the interval includes zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level α.
B) If the interval does not include zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level 100(1− α)%.
C) If the interval does not include zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level α.
D) If the interval includes zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level 100(1− α)%.
Question
When using Fisher's Least Significant Difference (LSD) where each interval has an error of α, the probability of committing a Type I error for at least one of the individual confidence intervals increases as the number of pairwise comparisons increases.
Question
Fisher's LSD method is applied when ________.

A) the ANOVA null hypothesis is rejected
B) the ANOVA null hypothesis is not rejected
C) either A or B occur
D) neither A or B occur
Question
Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μi - μj?

A) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px>
B) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px>
C) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px>
D) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px> j) ± tα,c-1
<strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <div style=padding-top: 35px>
Question
We use ANOVA to test for differences between population means by examining the amount of variability between the samples relative to the amount of variability within the samples.
Question
When the null hypothesis is rejected in an ANOVA test, Fisher's least significant difference method is superior to Tukey's honestly significant differences method to determine which population means differ.
Question
When two factors interact, the effect of one factor on the mean depends upon the specific value or level for the other factor.
Question
Which of the following is the assumption that is not applicable for a one-way ANOVA test?

A) The populations are normally distributed.
B) The population standard deviations are not all equal.
C) The samples are selected independently.
D) The sample is drawn at random from each population.
Question
One-way ANOVA is used to determine if differences exist between the means of three or more populations under dependent sampling.
Question
The between-treatments variance is the estimate of σ2 based on the variability due to chance.
Question
One-way ANOVA assumes the population standard deviations are unknown and assumed unequal.
Question
If there are five treatments under study, the number of pairwise comparisons is ________.

A) 15
B) 5
C) 20
D) 10
Question
The variability due to chance, also known as the within-treatments variance, is the estimate of σ2 which is not based on the variability ________.

A) between the sample means
B) due to random chance
C) within each sample
D) due to the common population variance
Question
In general, a blocking variable is used to eliminate the variability in the response due to the levels of the blocking variable.
Question
If the units within each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a randomized block design.
Question
When using Fisher's LSD method with a given significance level for each interval, the probability of committing a Type I error for at least one comparison increases as the number of ________.

A) pairwise comparisons decreases
B) pairwise comparisons increases
C) sample size increases
D) treatments decreases
Question
Using R, which of the below functions is used to generate an ANOVA table?

A) aov
B) anova
C) Tukey's HSD
D) None of the above
Question
The one-way ANOVA null hypothesis is rejected when the ________.

A) two estimates of the variance are relatively close together
B) variability in the sample means can be explained by chance
C) ratio of the within-treatments variance and the between-treatments variance is 1
D) ratio of the within-treatments variance and the between-treatments variance is significantly greater than 1
Question
The interaction test is performed before making any conclusions based on the tests for the main effects.
Question
One of the disadvantages of Fisher's LSD method is that the probability of committing at least one ________.

A) Type II error increases as the number of pairwise comparisons increases
B) Type I error increases as the number of pairwise comparisons decreases
C) Type II error increases as the number of pairwise comparisons decreases
D) Type I error increases as the number of pairwise comparisons increases
Question
Tukey's Honestly Significant Differences (HSD) method ensures that the probability of at least one Type I error remains fixed irrespective of the number of ________.

A) pairwise comparisons
B) treatments
C) replications within each treatment
D) replications for each combination of factor A and factor B
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The p-value of the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value of the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
If the interaction between two factors is not significant, the next tests to be done are ________.

A) none, the analysis is complete
B) none, gather more data
C) tests about the population means of factor A or factor B using two-way ANOVA without interaction
D) Tukey's confidence intervals
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The sum of squares due to treatments is ________.</strong> A) 10 B) 25 C) 75 D) 100 <div style=padding-top: 35px> The sum of squares due to treatments is ________.

A) 10
B) 25
C) 75
D) 100
Question
In a two-way ANOVA test, how many null hypotheses are tested?

A) 1
B) 1 or 2
C) 2 or 3
D) More than 3
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The mean square error is ________.</strong> A) 1.333 B) 9.375 C) 25 D) 75 <div style=padding-top: 35px> The mean square error is ________.

A) 1.333
B) 9.375
C) 25
D) 75
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the sum of squares due to treatments?</strong> A) 5,285.83 B) 13,281.79 C) 18,567.63 D) 4,427.26 <div style=padding-top: 35px> Which of the following is the sum of squares due to treatments?

A) 5,285.83
B) 13,281.79
C) 18,567.63
D) 4,427.26
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   For the within groups category, the degrees of freedom are ________.</strong> A) 6 B) 7 C) 8 D) 9 <div style=padding-top: 35px> For the within groups category, the degrees of freedom are ________.

A) 6
B) 7
C) 8
D) 9
Question
Tukey's 100(1 − α)% confidence interval for the difference between two population means μi - μj for balanced data is given by ________.

A) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px>
B) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px>
C) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px>
D) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px> <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <div style=padding-top: 35px>
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The competing hypotheses about the mean commute times are ________. </strong> A) H<sub>0</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub>, H<sub>A</sub>: Not all population means are equal B) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub> C) </sub><sub>H</sub><sub>0</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3 </sub>= ?<sub>4</sub>, H<sub>A</sub>: Not all population means are equal D) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub> = ?<sub>4</sub> <div style=padding-top: 35px>
The competing hypotheses about the mean commute times are ________.

A) H0: ?1 = ?2 = ?3, HA: Not all population means are equal
B) H0: Not all population means are equal, HA: ?1 = ?2 = ?3
C) H0: ?1 = ?2 = ?3 = ?4, HA: Not all population means are equal
D) H0: Not all population means are equal, HA: ?1 = ?2 = ?3 = ?4
Question
Which of the below is not true about Tukey's 100(1−α)% confidence interval for the difference between two population means?

A) Tukey's intervals are narrower than those based on Fisher's method.
B) Tukey's intervals are narrower than those based on the two-sample T method.
C) Tukey's intervals use a reduced significance level in comparison to Fisher's method
D) Tukey's intervals use an increased significance level in comparison to Fisher's method
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the sum of squared errors?</strong> A) 264.29 B) 5,285.83 C) 18,567.63 D) 13,281.79 <div style=padding-top: 35px> Which of the following is the sum of squared errors?

A) 264.29
B) 5,285.83
C) 18,567.63
D) 13,281.79
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The value of the test statistic is ________.</strong> A) 1.333 B) 9.375 C) 12.5 D) 100 <div style=padding-top: 35px> The value of the test statistic is ________.

A) 1.333
B) 9.375
C) 12.5
D) 100
Question
Tukey's HSD method uses ________ instead of ________ when compared to Fisher's LSD method for pairwise comparisons.

A) t values; studentized range values
B) studentized range values; F values
C) F values; t values
D) studentized range values; t values
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The value of the test statistic is ________.</strong> A) 0.06 B) 0.40 C) 2.51 D) 16.75 <div style=padding-top: 35px> The value of the test statistic is ________.

A) 0.06
B) 0.40
C) 2.51
D) 16.75
Question
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   At the 5% significance level, the critical value is ________.</strong> A) 3.11 B) 4.46 C) 6.06 D) 8.65 <div style=padding-top: 35px> At the 5% significance level, the critical value is ________.

A) 3.11
B) 4.46
C) 6.06
D) 8.65
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the mean square for treatments?</strong> A) 18,567.63 B) 13,281.79 C) 5,285.83 D) 4,427.26 <div style=padding-top: 35px> Which of the following is the mean square for treatments?

A) 18,567.63
B) 13,281.79
C) 5,285.83
D) 4,427.26
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   At the 5% significance level, the critical value is ________.</strong> A) 2.38 B) 3.10 C) 3.86 D) 4.94 <div style=padding-top: 35px> At the 5% significance level, the critical value is ________.

A) 2.38
B) 3.10
C) 3.86
D) 4.94
Question
Which of these null hypotheses is applicable for a two-way ANOVA test with interaction?

A) There is interaction between factors A and B.
B) Factor A and factor B means differ.
C) There is no interaction between factors A and B.
D) Factor A and factor B means do not differ.
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Based on the sample standard deviation, the one-way ANOVA assumption that is likely not met is ________.</strong> A) the populations are normally distributed. B) the population standard deviations are assumed to be equal. C) the samples are independent. D) None of these choices is correct. <div style=padding-top: 35px> Based on the sample standard deviation, the one-way ANOVA assumption that is likely not met is ________.

A) the populations are normally distributed.
B) the population standard deviations are assumed to be equal.
C) the samples are independent.
D) None of these choices is correct.
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The p-value for the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The Tukey's confidence intervals are shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The Tukey's confidence intervals are shown below.   At the 1% significance level, the conclusion from Tukey's confidence intervals is we ________.</strong> A) cannot conclude the mean number of crimes differs for West and East B) cannot conclude the mean number of crimes differs for West and South C) cannot conclude the mean number of crimes differs for South and North D) cannot conclude the mean number of crimes differs for West and North <div style=padding-top: 35px> At the 1% significance level, the conclusion from Tukey's confidence intervals is we ________.

A) cannot conclude the mean number of crimes differs for West and East
B) cannot conclude the mean number of crimes differs for West and South
C) cannot conclude the mean number of crimes differs for South and North
D) cannot conclude the mean number of crimes differs for West and North
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   At the 1% significance level, the conclusion for the hypothesis test is ________.</strong> A) reject the null hypothesis; we can conclude that not all mean number of crimes are equal B) do not reject the null hypothesis; we can conclude not all mean number of crimes are equal C) reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal D) do not reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal <div style=padding-top: 35px> At the 1% significance level, the conclusion for the hypothesis test is ________.

A) reject the null hypothesis; we can conclude that not all mean number of crimes are equal
B) do not reject the null hypothesis; we can conclude not all mean number of crimes are equal
C) reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal
D) do not reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor A?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor A?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <div style=padding-top: 35px> Which of the following is the value of the test statistic for factor A?

A) 4.76
B) 5.14
C) 9.41
D) 32.86
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below.   Which of these pairs of cities show a significant difference between the average commute times to work?</strong> A) Charlotte - Tucson B) Charlotte - Akron C) Houston - Charlotte D) Tucson- Akron <div style=padding-top: 35px> Which of these pairs of cities show a significant difference between the average commute times to work?

A) Charlotte - Tucson
B) Charlotte - Akron
C) Houston - Charlotte
D) Tucson- Akron
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher's 95% confidence intervals are shown below.   Which of these pair of cities show no significant difference between the average commute times to work?</strong> A) Houston, Akron B) Charlotte, Akron C) Charlotte, Tucson D) Houston, Tucson <div style=padding-top: 35px> Which of these pair of cities show no significant difference between the average commute times to work?

A) Houston, Akron
B) Charlotte, Akron
C) Charlotte, Tucson
D) Houston, Tucson
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below.   Which of the following is the studentized range value with α = 0.05 for Tukey's HSD method?</strong> A) 5.02 B) 3.58 C) 3.96 D) 4.64 <div style=padding-top: 35px> Which of the following is the studentized range value with α = 0.05 for Tukey's HSD method?

A) 5.02
B) 3.58
C) 3.96
D) 4.64
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The competing hypotheses about the mean crime rates are ________.</strong> A) H<sub>0</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3</sub>, H<sub>A</sub>: Not all population means are equal B) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3</sub> C) </sub><sub>H</sub><sub>0</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3 </sub>= μ<sub>4</sub>, H<sub>A</sub>: Not all population means are equal D) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3 </sub>= μ<sub>4</sub> <sub <div style=padding-top: 35px> The competing hypotheses about the mean crime rates are ________.

A) H0: μ1 = μ2 = μ3, HA: Not all population means are equal
B) H0: Not all population means are equal, HA: μ1 = μ2 = μ3
C) H0: μ1 = μ2 = μ3 = μ4, HA: Not all population means are equal
D) H0: Not all population means are equal, HA: μ1 = μ2 = μ3 = μ4
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The p-value for the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   Which of the following is the   value used to calculate the Fisher's 95% confidence intervals?</strong> A) 1.725 B) 2.086 C) 2.080 D) 2.090 <div style=padding-top: 35px> Which of the following is the <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   Which of the following is the   value used to calculate the Fisher's 95% confidence intervals?</strong> A) 1.725 B) 2.086 C) 2.080 D) 2.090 <div style=padding-top: 35px> value used to calculate the Fisher's 95% confidence intervals?

A) 1.725
B) 2.086
C) 2.080
D) 2.090
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 <div style=padding-top: 35px> How many degrees of freedom are there for factors A and B?

A) 2, 3
B) 3, 4
C) 3, 6
D) 2, 4
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below.   How many pairs of cities show a significant difference between the average commute times to work?</strong> A) 2 B) 3 C) 4 D) 6 <div style=padding-top: 35px> How many pairs of cities show a significant difference between the average commute times to work?

A) 2
B) 3
C) 4
D) 6
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor B?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor B?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <div style=padding-top: 35px> Which of the following is the value of the test statistic for factor B?

A) 4.76
B) 5.14
C) 9.41
D) 32.86
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   At the 1% significance level, the critical value is ________.</strong> A) 2.38 B) 3.10 C) 3.86 D) 4.94 <div style=padding-top: 35px> At the 1% significance level, the critical value is ________.

A) 2.38
B) 3.10
C) 3.86
D) 4.94
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   How many pairs of cities show a significant difference in average commute times to work?</strong> A) 2 B) 3 C) 4 D) 6 <div style=padding-top: 35px> How many pairs of cities show a significant difference in average commute times to work?

A) 2
B) 3
C) 4
D) 6
Question
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The conclusion for the hypothesis test is ________.</strong> A) to reject the null hypothesis; we cannot conclude that not all mean commute times are equal B) do not reject the null hypothesis; we cannot conclude that not all mean commute times are equal C) reject the null hypothesis; we can conclude that not all mean commute times are equal D) do not reject the null hypothesis; we can conclude that not all mean commute times are equal <div style=padding-top: 35px> The conclusion for the hypothesis test is ________.

A) to reject the null hypothesis; we cannot conclude that not all mean commute times are equal
B) do not reject the null hypothesis; we cannot conclude that not all mean commute times are equal
C) reject the null hypothesis; we can conclude that not all mean commute times are equal
D) do not reject the null hypothesis; we can conclude that not all mean commute times are equal
Question
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The degrees of freedom for the hypothesis test are ________.</strong> A) 4, 20 B) 3, 23 C) 3, 20 D) 4, 23 <div style=padding-top: 35px> The degrees of freedom for the hypothesis test are ________.

A) 4, 20
B) 3, 23
C) 3, 20
D) 4, 23
Question
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below.   The conclusion of the Tukey confidence intervals is ________.</strong> A) the mean commute time in Houston is different from the mean commute time in Charlotte, Tucson, and Akron B) the mean commute time in Charlotte is different from the mean commute time in Houston, Tucson, and Akron C) the mean commute time in Tucson is different from the mean commute time in Houston, Charlotte, and Akron D) the mean commute time in Akron is different from the mean time in Houston, Charlotte, and Tucson <div style=padding-top: 35px> The conclusion of the Tukey confidence intervals is ________.

A) the mean commute time in Houston is different from the mean commute time in Charlotte, Tucson, and Akron
B) the mean commute time in Charlotte is different from the mean commute time in Houston, Tucson, and Akron
C) the mean commute time in Tucson is different from the mean commute time in Houston, Charlotte, and Akron
D) the mean commute time in Akron is different from the mean time in Houston, Charlotte, and Tucson
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following are the total degrees of freedom?</strong> A) 10 B) 11 C) 12 D) 6 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following are the total degrees of freedom?</strong> A) 10 B) 11 C) 12 D) 6 <div style=padding-top: 35px> Which of the following are the total degrees of freedom?

A) 10
B) 11
C) 12
D) 6
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below   The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the hypothesis test about factor B is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 3.29 B) 4.76 C) 6.60 D) 9.78 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 3.29 B) 4.76 C) 6.60 D) 9.78 <div style=padding-top: 35px> At the 1% significance level, the critical value for the hypothesis test about factor B is ________.

A) 3.29
B) 4.76
C) 6.60
D) 9.78
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the hypothesis test about factor B is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of MSB?</strong> A) 15,623 B) 79,930 C) 37,170 D) 1,321,831 <div style=padding-top: 35px> Which of the following is the value of MSB?

A) 15,623
B) 79,930
C) 37,170
D) 1,321,831
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   For factor A, the value of the test statistic is ________.</strong> A) 3.21 B) 2.15 C) 16.43 D) 3 <div style=padding-top: 35px> For factor A, the value of the test statistic is ________.

A) 3.21
B) 2.15
C) 16.43
D) 3
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the hypothesis test about factor A is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.</strong> A) the average spending across spending B) the interaction between spending and generation C) the average spending across generation D) both the average spending across spending and generation <div style=padding-top: 35px> <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.</strong> A) the average spending across spending B) the interaction between spending and generation C) the average spending across generation D) both the average spending across spending and generation <div style=padding-top: 35px> For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.

A) the average spending across spending
B) the interaction between spending and generation
C) the average spending across generation
D) both the average spending across spending and generation
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of SSA?</strong> A) 46,869 B) 159,860 C) 1,115,101 D) 1,321,831 <div style=padding-top: 35px> Which of the following is the value of SSA?

A) 46,869
B) 159,860
C) 1,115,101
D) 1,321,831
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <div style=padding-top: 35px> The p-value for the hypothesis test about factor A is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level <div style=padding-top: 35px> At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.

A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level
B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level
C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level
D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 2.49 B) 3.32 C) 4.18 D) 5.39 <div style=padding-top: 35px> At the 5% significance level, the critical value for the hypothesis test about factor A is ________.

A) 2.49
B) 3.32
C) 4.18
D) 5.39
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location <div style=padding-top: 35px> At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.

A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location
B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location
C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location
D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 <div style=padding-top: 35px> How many degrees of freedom are there for factors A and B?

A) 2, 3
B) 3, 4
C) 3, 6
D) 2, 4
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The value of SSE is ________.</strong> A) 46,869 B) 159,860 C) 116,767 D) 1,321,831 <div style=padding-top: 35px> <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The value of SSE is ________.</strong> A) 46,869 B) 159,860 C) 116,767 D) 1,321,831 <div style=padding-top: 35px> The value of SSE is ________.

A) 46,869
B) 159,860
C) 116,767
D) 1,321,831
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The degrees of freedom for the interaction and the error are ________.</strong> A) 6, 24 B) 6, 30 C) 24, 6 D) 30, 6 <div style=padding-top: 35px> <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The degrees of freedom for the interaction and the error are ________.</strong> A) 6, 24 B) 6, 30 C) 24, 6 D) 30, 6 <div style=padding-top: 35px> The degrees of freedom for the interaction and the error are ________.

A) 6, 24
B) 6, 30
C) 24, 6
D) 30, 6
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of MSE?</strong> A) 15,623 B) 79,930 C) 37,170 D) 1,321,831 <div style=padding-top: 35px> Which of the following is the value of MSE?

A) 15,623
B) 79,930
C) 37,170
D) 1,321,831
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the conclusion of the hypothesis test for factor A is ________.</strong> A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by spending category B) do not reject the null hypothesis; we can conclude the average amount spent differs by spending category C) reject the null hypothesis; we cannot conclude the average amount spent differs by spending category D) reject the null hypothesis; we can conclude the average amount spent differs by spending category <div style=padding-top: 35px> At the 5% significance level, the conclusion of the hypothesis test for factor A is ________.

A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by spending category
B) do not reject the null hypothesis; we can conclude the average amount spent differs by spending category
C) reject the null hypothesis; we cannot conclude the average amount spent differs by spending category
D) reject the null hypothesis; we can conclude the average amount spent differs by spending category
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 2.28 B) 2.92 C) 3.59 D) 4.51 <div style=padding-top: 35px> At the 5% significance level, the critical value for the hypothesis test about factor B is ________.

A) 2.28
B) 2.92
C) 3.59
D) 4.51
Question
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the conclusion of the hypothesis test for Factor B is ________.</strong> A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by generation B) do not reject the null hypothesis; we can conclude the average amount spent differs by generation C) reject the null hypothesis; we cannot conclude the average amount spent differs by generation D) reject the null hypothesis; we can conclude the average amount spent differs by generation <div style=padding-top: 35px> At the 5% significance level, the conclusion of the hypothesis test for Factor B is ________.

A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by generation
B) do not reject the null hypothesis; we can conclude the average amount spent differs by generation
C) reject the null hypothesis; we cannot conclude the average amount spent differs by generation
D) reject the null hypothesis; we can conclude the average amount spent differs by generation
Question
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 3.46 B) 5.14 C) 7.26 D) 10.92 <div style=padding-top: 35px> <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 3.46 B) 5.14 C) 7.26 D) 10.92 <div style=padding-top: 35px> At the 5% significance level, the critical value for the hypothesis test about factor A is ________.

A) 3.46
B) 5.14
C) 7.26
D) 10.92
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Deck 13: Analysis of Variance
1
The between-treatments variance is based on a weighted sum of squared differences between the ________.

A) population variances and the overall mean of the data set
B) sample means and the overall mean of the data set
C) sample variances and the overall mean of the data set
D) population means and the overall mean of the data set
sample means and the overall mean of the data set
2
Which of the following is the correct interpretation of Fisher's 100(1 − α)% confidence interval for μi - μj?

A) If the interval includes zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level α.
B) If the interval does not include zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level 100(1− α)%.
C) If the interval does not include zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level α.
D) If the interval includes zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level 100(1− α)%.
If the interval does not include zero, the null hypothesis H0: μi - μj = 0, is rejected at a significance level α.
3
When using Fisher's Least Significant Difference (LSD) where each interval has an error of α, the probability of committing a Type I error for at least one of the individual confidence intervals increases as the number of pairwise comparisons increases.
True
4
Fisher's LSD method is applied when ________.

A) the ANOVA null hypothesis is rejected
B) the ANOVA null hypothesis is not rejected
C) either A or B occur
D) neither A or B occur
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5
Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μi - μj?

A) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>
B) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>
C) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   j) ± <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>
D) ( <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   i - <strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>   j) ± tα,c-1
<strong>Which of the following is the Fisher's 100(1− α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub>?</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ± t<sub>α,c</sub><sub>-1</sub> <sub> </sub>
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6
We use ANOVA to test for differences between population means by examining the amount of variability between the samples relative to the amount of variability within the samples.
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7
When the null hypothesis is rejected in an ANOVA test, Fisher's least significant difference method is superior to Tukey's honestly significant differences method to determine which population means differ.
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8
When two factors interact, the effect of one factor on the mean depends upon the specific value or level for the other factor.
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9
Which of the following is the assumption that is not applicable for a one-way ANOVA test?

A) The populations are normally distributed.
B) The population standard deviations are not all equal.
C) The samples are selected independently.
D) The sample is drawn at random from each population.
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10
One-way ANOVA is used to determine if differences exist between the means of three or more populations under dependent sampling.
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11
The between-treatments variance is the estimate of σ2 based on the variability due to chance.
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12
One-way ANOVA assumes the population standard deviations are unknown and assumed unequal.
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13
If there are five treatments under study, the number of pairwise comparisons is ________.

A) 15
B) 5
C) 20
D) 10
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14
The variability due to chance, also known as the within-treatments variance, is the estimate of σ2 which is not based on the variability ________.

A) between the sample means
B) due to random chance
C) within each sample
D) due to the common population variance
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15
In general, a blocking variable is used to eliminate the variability in the response due to the levels of the blocking variable.
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16
If the units within each block are randomly assigned to each of the treatments, then the design of the experiment is referred to as a randomized block design.
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17
When using Fisher's LSD method with a given significance level for each interval, the probability of committing a Type I error for at least one comparison increases as the number of ________.

A) pairwise comparisons decreases
B) pairwise comparisons increases
C) sample size increases
D) treatments decreases
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18
Using R, which of the below functions is used to generate an ANOVA table?

A) aov
B) anova
C) Tukey's HSD
D) None of the above
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19
The one-way ANOVA null hypothesis is rejected when the ________.

A) two estimates of the variance are relatively close together
B) variability in the sample means can be explained by chance
C) ratio of the within-treatments variance and the between-treatments variance is 1
D) ratio of the within-treatments variance and the between-treatments variance is significantly greater than 1
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20
The interaction test is performed before making any conclusions based on the tests for the main effects.
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21
One of the disadvantages of Fisher's LSD method is that the probability of committing at least one ________.

A) Type II error increases as the number of pairwise comparisons increases
B) Type I error increases as the number of pairwise comparisons decreases
C) Type II error increases as the number of pairwise comparisons decreases
D) Type I error increases as the number of pairwise comparisons increases
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22
Tukey's Honestly Significant Differences (HSD) method ensures that the probability of at least one Type I error remains fixed irrespective of the number of ________.

A) pairwise comparisons
B) treatments
C) replications within each treatment
D) replications for each combination of factor A and factor B
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23
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The p-value of the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value of the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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24
If the interaction between two factors is not significant, the next tests to be done are ________.

A) none, the analysis is complete
B) none, gather more data
C) tests about the population means of factor A or factor B using two-way ANOVA without interaction
D) Tukey's confidence intervals
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25
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The sum of squares due to treatments is ________.</strong> A) 10 B) 25 C) 75 D) 100 The sum of squares due to treatments is ________.

A) 10
B) 25
C) 75
D) 100
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26
In a two-way ANOVA test, how many null hypotheses are tested?

A) 1
B) 1 or 2
C) 2 or 3
D) More than 3
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27
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The mean square error is ________.</strong> A) 1.333 B) 9.375 C) 25 D) 75 The mean square error is ________.

A) 1.333
B) 9.375
C) 25
D) 75
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28
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the sum of squares due to treatments?</strong> A) 5,285.83 B) 13,281.79 C) 18,567.63 D) 4,427.26 Which of the following is the sum of squares due to treatments?

A) 5,285.83
B) 13,281.79
C) 18,567.63
D) 4,427.26
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29
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   For the within groups category, the degrees of freedom are ________.</strong> A) 6 B) 7 C) 8 D) 9 For the within groups category, the degrees of freedom are ________.

A) 6
B) 7
C) 8
D) 9
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30
Tukey's 100(1 − α)% confidence interval for the difference between two population means μi - μj for balanced data is given by ________.

A) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±
B) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±
C) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±
D) ( <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     i - <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     j) ± <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     <strong>Tukey's 100(1 − α)% confidence interval for the difference between two population means μ<sub>i</sub> - μ<sub>j</sub> for balanced data is given by ________.</strong> A) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     B) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     C) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±     D) (   <sub>i - </sub> <sub> </sub>   <sub>j</sub>) ±
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31
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The competing hypotheses about the mean commute times are ________. </strong> A) H<sub>0</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub>, H<sub>A</sub>: Not all population means are equal B) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub> C) </sub><sub>H</sub><sub>0</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3 </sub>= ?<sub>4</sub>, H<sub>A</sub>: Not all population means are equal D) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: ?<sub>1</sub> = ?<sub>2</sub> = ?<sub>3</sub> = ?<sub>4</sub>
The competing hypotheses about the mean commute times are ________.

A) H0: ?1 = ?2 = ?3, HA: Not all population means are equal
B) H0: Not all population means are equal, HA: ?1 = ?2 = ?3
C) H0: ?1 = ?2 = ?3 = ?4, HA: Not all population means are equal
D) H0: Not all population means are equal, HA: ?1 = ?2 = ?3 = ?4
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32
Which of the below is not true about Tukey's 100(1−α)% confidence interval for the difference between two population means?

A) Tukey's intervals are narrower than those based on Fisher's method.
B) Tukey's intervals are narrower than those based on the two-sample T method.
C) Tukey's intervals use a reduced significance level in comparison to Fisher's method
D) Tukey's intervals use an increased significance level in comparison to Fisher's method
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33
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the sum of squared errors?</strong> A) 264.29 B) 5,285.83 C) 18,567.63 D) 13,281.79 Which of the following is the sum of squared errors?

A) 264.29
B) 5,285.83
C) 18,567.63
D) 13,281.79
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34
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   The value of the test statistic is ________.</strong> A) 1.333 B) 9.375 C) 12.5 D) 100 The value of the test statistic is ________.

A) 1.333
B) 9.375
C) 12.5
D) 100
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35
Tukey's HSD method uses ________ instead of ________ when compared to Fisher's LSD method for pairwise comparisons.

A) t values; studentized range values
B) studentized range values; F values
C) F values; t values
D) studentized range values; t values
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36
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The value of the test statistic is ________.</strong> A) 0.06 B) 0.40 C) 2.51 D) 16.75 The value of the test statistic is ________.

A) 0.06
B) 0.40
C) 2.51
D) 16.75
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37
The following is an incomplete ANOVA table. <strong>The following is an incomplete ANOVA table.   At the 5% significance level, the critical value is ________.</strong> A) 3.11 B) 4.46 C) 6.06 D) 8.65 At the 5% significance level, the critical value is ________.

A) 3.11
B) 4.46
C) 6.06
D) 8.65
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38
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Which of the following is the mean square for treatments?</strong> A) 18,567.63 B) 13,281.79 C) 5,285.83 D) 4,427.26 Which of the following is the mean square for treatments?

A) 18,567.63
B) 13,281.79
C) 5,285.83
D) 4,427.26
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39
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   At the 5% significance level, the critical value is ________.</strong> A) 2.38 B) 3.10 C) 3.86 D) 4.94 At the 5% significance level, the critical value is ________.

A) 2.38
B) 3.10
C) 3.86
D) 4.94
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40
Which of these null hypotheses is applicable for a two-way ANOVA test with interaction?

A) There is interaction between factors A and B.
B) Factor A and factor B means differ.
C) There is no interaction between factors A and B.
D) Factor A and factor B means do not differ.
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41
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   Based on the sample standard deviation, the one-way ANOVA assumption that is likely not met is ________.</strong> A) the populations are normally distributed. B) the population standard deviations are assumed to be equal. C) the samples are independent. D) None of these choices is correct. Based on the sample standard deviation, the one-way ANOVA assumption that is likely not met is ________.

A) the populations are normally distributed.
B) the population standard deviations are assumed to be equal.
C) the samples are independent.
D) None of these choices is correct.
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42
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The p-value for the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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43
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The Tukey's confidence intervals are shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The Tukey's confidence intervals are shown below.   At the 1% significance level, the conclusion from Tukey's confidence intervals is we ________.</strong> A) cannot conclude the mean number of crimes differs for West and East B) cannot conclude the mean number of crimes differs for West and South C) cannot conclude the mean number of crimes differs for South and North D) cannot conclude the mean number of crimes differs for West and North At the 1% significance level, the conclusion from Tukey's confidence intervals is we ________.

A) cannot conclude the mean number of crimes differs for West and East
B) cannot conclude the mean number of crimes differs for West and South
C) cannot conclude the mean number of crimes differs for South and North
D) cannot conclude the mean number of crimes differs for West and North
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44
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   At the 1% significance level, the conclusion for the hypothesis test is ________.</strong> A) reject the null hypothesis; we can conclude that not all mean number of crimes are equal B) do not reject the null hypothesis; we can conclude not all mean number of crimes are equal C) reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal D) do not reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal At the 1% significance level, the conclusion for the hypothesis test is ________.

A) reject the null hypothesis; we can conclude that not all mean number of crimes are equal
B) do not reject the null hypothesis; we can conclude not all mean number of crimes are equal
C) reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal
D) do not reject the null hypothesis; we cannot conclude that not all mean number of crimes are equal
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45
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor A?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor A?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 Which of the following is the value of the test statistic for factor A?

A) 4.76
B) 5.14
C) 9.41
D) 32.86
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46
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below.   Which of these pairs of cities show a significant difference between the average commute times to work?</strong> A) Charlotte - Tucson B) Charlotte - Akron C) Houston - Charlotte D) Tucson- Akron Which of these pairs of cities show a significant difference between the average commute times to work?

A) Charlotte - Tucson
B) Charlotte - Akron
C) Houston - Charlotte
D) Tucson- Akron
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47
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher's 95% confidence intervals are shown below.   Which of these pair of cities show no significant difference between the average commute times to work?</strong> A) Houston, Akron B) Charlotte, Akron C) Charlotte, Tucson D) Houston, Tucson Which of these pair of cities show no significant difference between the average commute times to work?

A) Houston, Akron
B) Charlotte, Akron
C) Charlotte, Tucson
D) Houston, Tucson
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48
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey 95% confidence intervals are shown below.   Which of the following is the studentized range value with α = 0.05 for Tukey's HSD method?</strong> A) 5.02 B) 3.58 C) 3.96 D) 4.64 Which of the following is the studentized range value with α = 0.05 for Tukey's HSD method?

A) 5.02
B) 3.58
C) 3.96
D) 4.64
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49
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The competing hypotheses about the mean crime rates are ________.</strong> A) H<sub>0</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3</sub>, H<sub>A</sub>: Not all population means are equal B) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3</sub> C) </sub><sub>H</sub><sub>0</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3 </sub>= μ<sub>4</sub>, H<sub>A</sub>: Not all population means are equal D) H<sub>0</sub>: Not all population means are equal, H<sub>A</sub>: μ<sub>1</sub> = μ<sub>2</sub> = μ<sub>3 </sub>= μ<sub>4</sub> <sub The competing hypotheses about the mean crime rates are ________.

A) H0: μ1 = μ2 = μ3, HA: Not all population means are equal
B) H0: Not all population means are equal, HA: μ1 = μ2 = μ3
C) H0: μ1 = μ2 = μ3 = μ4, HA: Not all population means are equal
D) H0: Not all population means are equal, HA: μ1 = μ2 = μ3 = μ4
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50
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The p-value for the test is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the test is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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51
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   Which of the following is the   value used to calculate the Fisher's 95% confidence intervals?</strong> A) 1.725 B) 2.086 C) 2.080 D) 2.090 Which of the following is the <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   Which of the following is the   value used to calculate the Fisher's 95% confidence intervals?</strong> A) 1.725 B) 2.086 C) 2.080 D) 2.090 value used to calculate the Fisher's 95% confidence intervals?

A) 1.725
B) 2.086
C) 2.080
D) 2.090
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52
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 How many degrees of freedom are there for factors A and B?

A) 2, 3
B) 3, 4
C) 3, 6
D) 2, 4
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53
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below.   How many pairs of cities show a significant difference between the average commute times to work?</strong> A) 2 B) 3 C) 4 D) 6 How many pairs of cities show a significant difference between the average commute times to work?

A) 2
B) 3
C) 4
D) 6
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54
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor B?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following is the value of the test statistic for factor B?</strong> A) 4.76 B) 5.14 C) 9.41 D) 32.86 Which of the following is the value of the test statistic for factor B?

A) 4.76
B) 5.14
C) 9.41
D) 32.86
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55
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South(4) sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   At the 1% significance level, the critical value is ________.</strong> A) 2.38 B) 3.10 C) 3.86 D) 4.94 At the 1% significance level, the critical value is ________.

A) 2.38
B) 3.10
C) 3.86
D) 4.94
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56
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Fisher 95% confidence intervals are shown below.   How many pairs of cities show a significant difference in average commute times to work?</strong> A) 2 B) 3 C) 4 D) 6 How many pairs of cities show a significant difference in average commute times to work?

A) 2
B) 3
C) 4
D) 6
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57
A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625. <strong>A researcher with the Ministry of Transportation is commissioned to study the drive times to work (one-way) for U.S. cities. The underlying hypothesis is that average commute times are different across cities. To test the hypothesis, the researcher randomly selects six people from each of the four cities and records their one-way commute times to work. Refer to the below data on one-way commute times (in minutes) to work. Note that the grand mean is 36.625.   The conclusion for the hypothesis test is ________.</strong> A) to reject the null hypothesis; we cannot conclude that not all mean commute times are equal B) do not reject the null hypothesis; we cannot conclude that not all mean commute times are equal C) reject the null hypothesis; we can conclude that not all mean commute times are equal D) do not reject the null hypothesis; we can conclude that not all mean commute times are equal The conclusion for the hypothesis test is ________.

A) to reject the null hypothesis; we cannot conclude that not all mean commute times are equal
B) do not reject the null hypothesis; we cannot conclude that not all mean commute times are equal
C) reject the null hypothesis; we can conclude that not all mean commute times are equal
D) do not reject the null hypothesis; we can conclude that not all mean commute times are equal
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58
A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below. <strong>A police chief wants to determine if crime rates are different for four different areas of the city (East(1), West(2), North(3), and South sides), and obtains data on the number of crimes per day in each area. The one-way ANOVA table is shown below.   The degrees of freedom for the hypothesis test are ________.</strong> A) 4, 20 B) 3, 23 C) 3, 20 D) 4, 23 The degrees of freedom for the hypothesis test are ________.

A) 4, 20
B) 3, 23
C) 3, 20
D) 4, 23
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59
The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below. <strong>The ANOVA test performed for determined that not all mean commute times across the four cities are equal. However, it did not indicate which means differed. To find out which population means differ requires further analysis of the direction and the statistical significance of the difference between paired population means. Tukey's 95% confidence intervals are shown below.   The conclusion of the Tukey confidence intervals is ________.</strong> A) the mean commute time in Houston is different from the mean commute time in Charlotte, Tucson, and Akron B) the mean commute time in Charlotte is different from the mean commute time in Houston, Tucson, and Akron C) the mean commute time in Tucson is different from the mean commute time in Houston, Charlotte, and Akron D) the mean commute time in Akron is different from the mean time in Houston, Charlotte, and Tucson The conclusion of the Tukey confidence intervals is ________.

A) the mean commute time in Houston is different from the mean commute time in Charlotte, Tucson, and Akron
B) the mean commute time in Charlotte is different from the mean commute time in Houston, Tucson, and Akron
C) the mean commute time in Tucson is different from the mean commute time in Houston, Charlotte, and Akron
D) the mean commute time in Akron is different from the mean time in Houston, Charlotte, and Tucson
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60
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following are the total degrees of freedom?</strong> A) 10 B) 11 C) 12 D) 6 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     Which of the following are the total degrees of freedom?</strong> A) 10 B) 11 C) 12 D) 6 Which of the following are the total degrees of freedom?

A) 10
B) 11
C) 12
D) 6
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61
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below   The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the hypothesis test about factor B is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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62
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 3.29 B) 4.76 C) 6.60 D) 9.78 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 3.29 B) 4.76 C) 6.60 D) 9.78 At the 1% significance level, the critical value for the hypothesis test about factor B is ________.

A) 3.29
B) 4.76
C) 6.60
D) 9.78
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63
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor B is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the hypothesis test about factor B is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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64
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of MSB?</strong> A) 15,623 B) 79,930 C) 37,170 D) 1,321,831 Which of the following is the value of MSB?

A) 15,623
B) 79,930
C) 37,170
D) 1,321,831
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65
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   For factor A, the value of the test statistic is ________.</strong> A) 3.21 B) 2.15 C) 16.43 D) 3 For factor A, the value of the test statistic is ________.

A) 3.21
B) 2.15
C) 16.43
D) 3
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66
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the hypothesis test about factor A is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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67
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.</strong> A) the average spending across spending B) the interaction between spending and generation C) the average spending across generation D) both the average spending across spending and generation <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.</strong> A) the average spending across spending B) the interaction between spending and generation C) the average spending across generation D) both the average spending across spending and generation For the analysis with an interaction between spending category and generation, the first hypothesis test to conduct should be about ________.

A) the average spending across spending
B) the interaction between spending and generation
C) the average spending across generation
D) both the average spending across spending and generation
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68
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of SSA?</strong> A) 46,869 B) 159,860 C) 1,115,101 D) 1,321,831 Which of the following is the value of SSA?

A) 46,869
B) 159,860
C) 1,115,101
D) 1,321,831
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69
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   The p-value for the hypothesis test about factor A is ________.</strong> A) less than 0.01 B) between 0.01 and 0.025 C) between 0.025 and 0.05 D) greater than 0.05 The p-value for the hypothesis test about factor A is ________.

A) less than 0.01
B) between 0.01 and 0.025
C) between 0.025 and 0.05
D) greater than 0.05
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70
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level At the 5% significance level, the conclusion for the hypothesis test about factor A is ________.

A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by income level
B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level
C) reject the null hypothesis; we can conclude the average mortgage payments differ by income level
D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by income level
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71
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 2.49 B) 3.32 C) 4.18 D) 5.39 At the 5% significance level, the critical value for the hypothesis test about factor A is ________.

A) 2.49
B) 3.32
C) 4.18
D) 5.39
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72
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.</strong> A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location At the 1% significance level, the conclusion for the hypothesis test about factor B is ________.

A) do not reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location
B) do not reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location
C) reject the null hypothesis; we can conclude the average mortgage payments differ by zonal location
D) reject the null hypothesis; we cannot conclude the average mortgage payments differ by zonal location
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73
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   How many degrees of freedom are there for factors A and B?</strong> A) 2, 3 B) 3, 4 C) 3, 6 D) 2, 4 How many degrees of freedom are there for factors A and B?

A) 2, 3
B) 3, 4
C) 3, 6
D) 2, 4
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74
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The value of SSE is ________.</strong> A) 46,869 B) 159,860 C) 116,767 D) 1,321,831 <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The value of SSE is ________.</strong> A) 46,869 B) 159,860 C) 116,767 D) 1,321,831 The value of SSE is ________.

A) 46,869
B) 159,860
C) 116,767
D) 1,321,831
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75
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The degrees of freedom for the interaction and the error are ________.</strong> A) 6, 24 B) 6, 30 C) 24, 6 D) 30, 6 <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers). The data and an incomplete ANOVA table are shown below.     The degrees of freedom for the interaction and the error are ________.</strong> A) 6, 24 B) 6, 30 C) 24, 6 D) 30, 6 The degrees of freedom for the interaction and the error are ________.

A) 6, 24
B) 6, 30
C) 24, 6
D) 30, 6
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76
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   Which of the following is the value of MSE?</strong> A) 15,623 B) 79,930 C) 37,170 D) 1,321,831 Which of the following is the value of MSE?

A) 15,623
B) 79,930
C) 37,170
D) 1,321,831
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77
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the conclusion of the hypothesis test for factor A is ________.</strong> A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by spending category B) do not reject the null hypothesis; we can conclude the average amount spent differs by spending category C) reject the null hypothesis; we cannot conclude the average amount spent differs by spending category D) reject the null hypothesis; we can conclude the average amount spent differs by spending category At the 5% significance level, the conclusion of the hypothesis test for factor A is ________.

A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by spending category
B) do not reject the null hypothesis; we can conclude the average amount spent differs by spending category
C) reject the null hypothesis; we cannot conclude the average amount spent differs by spending category
D) reject the null hypothesis; we can conclude the average amount spent differs by spending category
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78
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the critical value for the hypothesis test about factor B is ________.</strong> A) 2.28 B) 2.92 C) 3.59 D) 4.51 At the 5% significance level, the critical value for the hypothesis test about factor B is ________.

A) 2.28
B) 2.92
C) 3.59
D) 4.51
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79
A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below. <strong>A market researcher is studying the spending habits of people across age groups. The amount of money spent by each individual is classified by spending category (Dining out, Shopping, or Electronics) - Factor A, and generation (Gen-X, Gen-Y, Gen-Z, or Baby Boomers) - Factor B. An incomplete ANOVA table is shown below.   At the 5% significance level, the conclusion of the hypothesis test for Factor B is ________.</strong> A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by generation B) do not reject the null hypothesis; we can conclude the average amount spent differs by generation C) reject the null hypothesis; we cannot conclude the average amount spent differs by generation D) reject the null hypothesis; we can conclude the average amount spent differs by generation At the 5% significance level, the conclusion of the hypothesis test for Factor B is ________.

A) do not reject the null hypothesis; we cannot conclude the average amount spent differs by generation
B) do not reject the null hypothesis; we can conclude the average amount spent differs by generation
C) reject the null hypothesis; we cannot conclude the average amount spent differs by generation
D) reject the null hypothesis; we can conclude the average amount spent differs by generation
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80
A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below. <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 3.46 B) 5.14 C) 7.26 D) 10.92 <strong>A researcher wants to understand how an annual mortgage payment (in dollars) depends on income level and zonal location using a two-way ANOVA without interaction. The data and an incomplete ANOVA table are shown below.     At the 5% significance level, the critical value for the hypothesis test about factor A is ________.</strong> A) 3.46 B) 5.14 C) 7.26 D) 10.92 At the 5% significance level, the critical value for the hypothesis test about factor A is ________.

A) 3.46
B) 5.14
C) 7.26
D) 10.92
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Unlock Deck
Unlock for access to all 120 flashcards in this deck.