Consider the following ANOVA table. \(\begin{array}{llll} \begin{array}{l} \text { Source } \\ \text { of Variation } \end{array} & \begin{array}{l} \text { Sum } \\ \text { of Squares } \end{array} & \begin{array}{l} \text { Degrees } \\ \text { of Freed om } \end{array} & \begin{array}{l} \text { Mean } \\ \text { Square } \end{array}&F \\ \text { Between Treatments } & 2073.6 & 4 & \\ \text { Between Blocks } & 6000 & 5 & 1200 \\ \text { Error } & & 20 & 288 \\ \text { Total } & & 29 & \end{array}\) The mean square due to treatments equals

A) 288. B) 518.4. C) 1200. D) 8294.4. A) 288. B) 518.4. C) 1200. D) 8294.4.

Part of an ANOVA table is shown below. \[\begin{array} { l l l l l } \text { Source of } & \text { Sum of } & \text { Degrees of } & \text { Mean } \\ \text { Variation } & \text { Squares } & \text { Freedom } & \text { Square } & F \\ \text { Between Treatments } & 180 & 3 & \\ \text { Within Treatments (Error) } & & & \\ \text { TOTAL } & 480 & 18 & \end{array}\] The test statistic is

A) 2.25. B) 6.00. C) 2.67. D) 3.00. A) 2.25. B) 6.00. C) 2.67. D) 3.00.

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. \(\begin{array}{lllll} \text { Treatment } &&{\text { Observations }} \\ \text { A } & 20 & 30 & 25 & 33 \\ \text { B } & 22 & 26 & 20 & 28 \\ \mathrm{C} & 40 & 30 & 28 & 22 \end{array}\) The mean square due to treatments (MSTR) equals

A) 1.872. B) 5.86. C) 34. D) 36. A) 1.872. B) 5.86. C) 34. D) 36.

In a completely randomized design involving three treatments, the following information is provided: \[\begin{array} { l l l l } & \text { Treatment 1 } & \text { Treatment 2 } & \text { Treatment 3 } \\ \text { Sample Size } & 5 & 10 & 5 \\ \text { Sample Mean } & 4 & 8 & 9 \end{array}\] The overall mean (the grand mean) for all the treatments is

A) 7.00. B) 6.67. C) 7.25. D) 4.89. A) 7.00. B) 6.67. C) 7.25. D) 4.89.

Consider the following ANOVA table. \[\begin{array} { l l l l } \text { Source } & \text { Sum } & \text { Degrees } & \text { Mean } \\ \text { of Variation } & \text { of Squares } & \text { of Freedom } & \text { Square } \\ \text { Between Treatments } & 2073.6 & 4 & \\ \text { Between Blocks } & 6000 & 5 & 1200 \\ \text { Error } & & 20 & 288 \\ \text { Total } & & 29 & \end{array}\] The null hypothesis for this ANOVA problem is

A) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4. B) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4 = \(\mu\)5. C) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4 = \(\mu\)5 =\(\mu\)6. D) \(\mu\)1 = \(\mu\)2 = ... = \(\mu\)20. A) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4. B) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4 = \(\mu\)5. C) \(\mu\)1 = \(\mu\)2 = \(\mu\)3 = \(\mu\)4 = \(\mu\)5 =\(\mu\)6. D) \(\mu\)1 = \(\mu\)2 = ... = \(\mu\)20.

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. \(\begin{array}{lllll} \text { Treatment } &&{\text { Observations }} \\ \text { A } & 20 & 30 & 25 & 33 \\ \text { B } & 22 & 26 & 20 & 28 \\ \mathrm{C} & 40 & 30 & 28 & 22 \end{array}\) The test statistic to test the null hypothesis equals

A) .944. B) 1.06. C) 3.13. D) 19.231. A) .944. B) 1.06. C) 3.13. D) 19.231.

Consider the following ANOVA table. \(\begin{array}{llll} \begin{array}{l} \text { Source } \\ \text { of Variation } \end{array} & \begin{array}{l} \text { Sum } \\ \text { of Squares } \end{array} & \begin{array}{l} \text { Degrees } \\ \text { of Freed om } \end{array} & \begin{array}{l} \text { Mean } \\ \text { Square } \end{array}&F \\ \text { Between Treatments } & 2073.6 & 4 & \\ \text { Between Blocks } & 6000 & 5 & 1200 \\ \text { Error } & & 20 & 288 \\ \text { Total } & & 29 & \end{array}\) The null hypothesis is to be tested at the 5% level of significance.The null hypothesis

A) should be rejected. B) should not be rejected. C) should be revised. D) should not be tested. A) should be rejected. B) should not be rejected. C) should be revised. D) should not be tested.

Consider the following information. \(\begin{array}{ll} \mathrm{SSTR}=6750 & H 0: \mu 1=\mu 2=\mu 3=\mu 4 \\ \mathrm{SSE}=8000 & H_{\mathrm{a}}: \text { At least one mean is different } \end{array}\) If n = 5, the mean square due to error (MSE) equals

A) 400. B) 500. C) 1687.5. D) 2250. A) 400. B) 500. C) 1687.5. D) 2250.

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. \(\begin{array}{lllll} \text { Treatment } &&{\text { Observations }} \\ \text { A } & 20 & 30 & 25 & 33 \\ \text { B } & 22 & 26 & 20 & 28 \\ \mathrm{C} & 40 & 30 & 28 & 22 \end{array}\) The null hypothesis is to be tested at the 1% level of significance.The p-value is

A) greater than .1. B) between .05 to .10. C) less than .01. D) between .01 to .025. A) greater than .1. B) between .05 to .10. C) less than .01. D) between .01 to .025.

Exam 13: Experimental Design and Analysis of Variance

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The mean square due to treatments equals

(Multiple Choice)

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Question 41

Part of an ANOVA table is shown below. Source of Sum of Degrees of Mean Variation Squares Freedom Square F Between Treatments 180 3 Within Treatments (Error) TOTAL 480 18 The test statistic is

(Multiple Choice)

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Question 42

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. Treatment Observations A 20 30 25 33 B 22 26 20 28 40 30 28 22 The mean square due to treatments (MSTR) equals

(Multiple Choice)

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Question 43

In a completely randomized design involving three treatments, the following information is provided: Treatment 1 Treatment 2 Treatment 3 Sample Size 5 10 5 Sample Mean 4 8 9 The overall mean (the grand mean) for all the treatments is

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Question 44

Consider the following ANOVA table. Source Sum Degrees Mean of Variation of Squares of Freedom Square Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis for this ANOVA problem is

(Multiple Choice)

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Question 45

In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations).Also, the design provided the following information. SSTR = 200 (Sum of Squares Due to Treatments) SST = 800 (Total Sum of Squares) The mean square due to error (MSE) is

(Multiple Choice)

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Question 46

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. Treatment Observations A 20 30 25 33 B 22 26 20 28 40 30 28 22 The test statistic to test the null hypothesis equals

(Multiple Choice)

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Question 47

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis is to be tested at the 5% level of significance.The null hypothesis

(Multiple Choice)

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Question 48

The number of times each experimental condition is observed in a factorial design is known as

(Multiple Choice)

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Question 49

In ANOVA, which of the following is not affected by whether or not the population means are equal?

(Multiple Choice)

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Question 50

In the ANOVA, treatments refer to

(Multiple Choice)

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Question 51

Consider the following information. =6750 H0:\mu1=\mu2=\mu3=\mu4 =8000 : At least one mean is different If n = 5, the mean square due to error (MSE) equals

(Multiple Choice)

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Question 52

The process of allocating the total sum of squares and degrees of freedom to the various components is called

(Multiple Choice)

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Question 53

Consider the following information. SSTR = 6750 H₀: μ₁ =μ₂ =μ₃ =μ₄ SSE = 8000 H_a: At least one mean is different The null hypothesis is to be tested at the 5% level of significance.The p-value is

(Multiple Choice)

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Question 54

In a factorial experiment, if there are x levels of factor A and y levels of factor B, there is a total of

(Multiple Choice)

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Question 55

If we are testing for the equality of three population means, we should use the

(Multiple Choice)

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Question 56

The independent variable of interest in an ANOVA procedure is called a

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Question 57

In the analysis of variance procedure (ANOVA), "factor" refers to

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Question 58

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. Treatment Observations A 20 30 25 33 B 22 26 20 28 40 30 28 22 The null hypothesis is to be tested at the 1% level of significance.The p-value is

(Multiple Choice)

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Question 59

The F ratio in a completely randomized ANOVA is given by

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Question 60

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The mean square due to treatments equals

Part of an ANOVA table is shown below. Source of Sum of Degrees of Mean Variation Squares Freedom Square F Between Treatments 180 3 Within Treatments (Error) TOTAL 480 18 The test statistic is

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. Treatment Observations A 20 30 25 33 B 22 26 20 28 40 30 28 22 The mean square due to treatments (MSTR) equals

In a completely randomized design involving three treatments, the following information is provided: Treatment 1 Treatment 2 Treatment 3 Sample Size 5 10 5 Sample Mean 4 8 9 The overall mean (the grand mean) for all the treatments is

Consider the following ANOVA table. Source Sum Degrees Mean of Variation of Squares of Freedom Square Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis for this ANOVA problem is

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis is to be tested at the 5% level of significance.The null hypothesis

The number of times each experimental condition is observed in a factorial design is known as

In ANOVA, which of the following is not affected by whether or not the population means are equal?

In the ANOVA, treatments refer to

Consider the following information. =6750 H0:\mu1=\mu2=\mu3=\mu4 =8000 : At least one mean is different If n = 5, the mean square due to error (MSE) equals

The process of allocating the total sum of squares and degrees of freedom to the various components is called

Consider the following information. SSTR = 6750 H₀: μ₁ =μ₂ =μ₃ =μ₄ SSE = 8000 H_a: At least one mean is different The null hypothesis is to be tested at the 5% level of significance.The p-value is

In a factorial experiment, if there are x levels of factor A and y levels of factor B, there is a total of

If we are testing for the equality of three population means, we should use the

The independent variable of interest in an ANOVA procedure is called a

In the analysis of variance procedure (ANOVA), "factor" refers to

The F ratio in a completely randomized ANOVA is given by

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Simple Linear Regression

Multiple Regression

Filters

Exam 13: Experimental Design and Analysis of Variance

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The mean square due to treatments equals

Part of an ANOVA table is shown below. Source of Sum of Degrees of Mean Variation Squares Freedom Square F Between Treatments 180 3 Within Treatments (Error) TOTAL 480 18 The test statistic is

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.You are given the results below. Treatment Observations A 20 30 25 33 B 22 26 20 28 40 30 28 22 The mean square due to treatments (MSTR) equals

In a completely randomized design involving three treatments, the following information is provided: Treatment 1 Treatment 2 Treatment 3 Sample Size 5 10 5 Sample Mean 4 8 9 The overall mean (the grand mean) for all the treatments is

Consider the following ANOVA table. Source Sum Degrees Mean of Variation of Squares of Freedom Square Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis for this ANOVA problem is

Consider the following ANOVA table. Source of Variation Sum of Squares Degrees of Freed om Mean Square F Between Treatments 2073.6 4 Between Blocks 6000 5 1200 Error 20 288 Total 29 The null hypothesis is to be tested at the 5% level of significance.The null hypothesis

The number of times each experimental condition is observed in a factorial design is known as

In ANOVA, which of the following is not affected by whether or not the population means are equal?

In the ANOVA, treatments refer to

Consider the following information. =6750 H0:\mu1=\mu2=\mu3=\mu4 =8000 : At least one mean is different If n = 5, the mean square due to error (MSE) equals

The process of allocating the total sum of squares and degrees of freedom to the various components is called

Consider the following information. ​ SSTR = 6750 H0: μ1 = μ2 = μ3 = μ4 SSE = 8000 Ha: At least one mean is different ​ The null hypothesis is to be tested at the 5% level of significance.The p-value is

In a factorial experiment, if there are x levels of factor A and y levels of factor B, there is a total of​

If we are testing for the equality of three population means, we should use the​

The independent variable of interest in an ANOVA procedure is called a

In the analysis of variance procedure (ANOVA), "factor" refers to

The F ratio in a completely randomized ANOVA is given by

Data and Statistics

Descriptive Statistics: Tabulargraphical

Descriptive Statistics: Numerical

Introduction to Probability

Discrete Probability Distributions

Continuous Probability Distributions

Sampling and Sampling Distributions

Interval Estimation

Hypothesis Tests

Inference About Means and Proportions With Two Populations

Inferences About Population Variances

Comparing Multiple Proportions, Test of Independence and Goodness of Fit

Simple Linear Regression

Multiple Regression

Filters

Consider the following information. SSTR = 6750 H₀: μ₁ =μ₂ =μ₃ =μ₄ SSE = 8000 H_a: At least one mean is different The null hypothesis is to be tested at the 5% level of significance.The p-value is

In a factorial experiment, if there are x levels of factor A and y levels of factor B, there is a total of

If we are testing for the equality of three population means, we should use the