For the data in the source table, what decision can be made about the hypotheses being tested? \[\begin{array} { l | c | c c | c | } \hline \text { Source } & S S & d f & M S & F \\ \hline \text { Between-groups } & 39.52 & 2 & 19.76 & \\ \hline \text { Subjects } & 6.45 & 5 & 1.29 & \\ \hline \text { Within-groups } & 19.93 & 10 & 1.993 & \\ \hline \text { Total } & 53 & 17 & & \\ \hline \end{array}\]

A) Fail to reject the null hypothesis because the F statistic does not exceed the critical cutoff. B) Fail to reject the null hypothesis and conclude there is no effect of the independent variable. C) Reject the null hypothesis and conclude there are differences among the levels of the independent variable. D) Reject the null hypothesis and conclude the independent variable has no effect. A) Fail to reject the null hypothesis because the F statistic does not exceed the critical cutoff. B) Fail to reject the null hypothesis and conclude there is no effect of the independent variable. C) Reject the null hypothesis and conclude there are differences among the levels of the independent variable. D) Reject the null hypothesis and conclude the independent variable has no effect.

For the data in the ANOVA source table, what is the effect size? \[\begin{array} { l l | l | l | l | } \hline \text { Source } & \text { SS } & d f & M S & F \\ \hline \text { Between-groups } & 13.72 & 2 & 6.86 & 7.831 \\ \hline \text { Subjects } & 9.01 & 5 & 1.802 & 2.057 \\ \hline \text { Within-groups } & 8.76 & 10 & 0.876 & \\ \hline \text { Total } & 24.49 & 17 & & \\ \hline \end{array}\]

A) small B) medium C) large D) very large A) small B) medium C) large D) very large

For the data in the source table, calculate the F statistic of interest to researchers. \[\begin{array} { l c c | c c } \hline \text { Source } & S S & d f & M S & F \\ \hline \text { Between-groups } & 12.159 & 3 & 4.053 \\ \hline \text { Subjects } & 6.77 & 5 & 1.354 \\ \hline \text { Within-groups } & 20.4 & 15 & 1.360 \\ \hline \text { Total } & 39.329 & 23 & \\ \hline \end{array}\]

A) 0.34 B) 1.00 C) 2.98 D) 2.99 A) 0.34 B) 1.00 C) 2.98 D) 2.99

Exam 13: One-Way Within-Groups Anova

A researcher wants to examine people's preference for pets by having 10 people act as "foster owners" for four different types of family pets: dogs, cats, birds, and fish.The participants will foster each type of pet for one week, and a scale measure will be used to assess preference.Which research design should be used?

(Multiple Choice)

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Question 61

For the data in the source table, what decision can be made about the hypotheses being tested? Source SS df MS F Between-groups 39.52 2 19.76 Subjects 6.45 5 1.29 Within-groups 19.93 10 1.993 Total 53 17

(Multiple Choice)

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Question 62

A researcher wants to take advantage of the strengths of a within-groups design but does not want to have each participant experience all levels of the independent variable.She can accomplish this through what other design option?

(Multiple Choice)

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Question 63

The Tukey HSD test helps us determine which means are statistically significantly different from each other in a within-groups ANOVA.

(True/False)

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Question 64

The primary benefit of the within-groups design is that between-groups variability is reduced.

(True/False)

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Question 65

The multiple-group equivalent of a paired-samples t test is the:

(Multiple Choice)

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Question 66

When using a one-way within-groups ANOVA, the variability due to individual differences is _, resulting in a _ F statistic.

(Multiple Choice)

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Question 67

According to Cohen's conventions, an effect size of 0.062 for a one-way within-groups ANOVA is considered to be:

(Multiple Choice)

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Question 68

Pet preference was compared for four different types of animals (dogs, cats, birds, and fish), using a one-way within-groups ANOVA with nine participants.The standard error was calculated as 0.19.A significant F test indicates that there are differences between the groups.What post hoc tests are you most interested in performing given these group means: Dogs M = 4.43, Cats M = 4.18, Birds M = 2.73, Fish M = 4.07?

(Multiple Choice)

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Question 69

The one-way within-groups ANOVA has an additional assumption compared to the between-groups ANOVA.Which assumption is unique to the within-groups ANOVA?

(Multiple Choice)

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Question 70

The effect size measure for the one-way within-groups ANOVA is Cohen's d.

(True/False)

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Question 71

When conducting the one-way within-groups ANOVA, two F statistics are calculated, but only one is of primary interest.

(True/False)

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Question 72

A researcher interested in the impact of "dress-down Fridays" on work performance decides to study the impact of attire at work.She randomly selects 35 people at a large company to participate.Over the course of three weeks, she has all 35 participants experience working under three different levels of work attire: casual, dress-casual, and formal attire.What statistical analysis would be appropriate for her design?

(Multiple Choice)

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Question 73

Each participant experiences all levels of the independent variable in a within-groups design.

(True/False)

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Question 74

Within-groups variability is reduced in the one-way within-groups ANOVA because:

(Multiple Choice)

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Question 75

A researcher examines the effectiveness of different body lotions by having 12 participants apply four different lotions to the same, unique body locations daily for two weeks.For example, lotion #1 is always applied to the right thigh, while lotion #2 is applied to the upper right arm.The participants were randomly selected at a drugstore in a busy area.What is the null hypothesis for this study?

(Multiple Choice)

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Question 76

Matched groups require participants who are similar on all the variables that the researcher wants to control.

(True/False)

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Question 77

For the data in the ANOVA source table, what is the effect size? Source SS df MS F Between-groups 13.72 2 6.86 7.831 Subjects 9.01 5 1.802 2.057 Within-groups 8.76 10 0.876 Total 24.49 17

(Multiple Choice)

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Question 78

Although the hypothesis test can provide the probability that the levels of the independent variable lead to differences in the dependent variable, it is important to calculate effect size to:

(Multiple Choice)

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Question 79

For the data in the source table, calculate the F statistic of interest to researchers. Source SS df MS F Between-groups 12.159 3 4.053 Subjects 6.77 5 1.354 Within-groups 20.4 15 1.360 Total 39.329 23

(Multiple Choice)

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Question 80

Showing 61 - 80 of 102

For the data in the source table, what decision can be made about the hypotheses being tested? Source SS df MS F Between-groups 39.52 2 19.76 Subjects 6.45 5 1.29 Within-groups 19.93 10 1.993 Total 53 17

A researcher wants to take advantage of the strengths of a within-groups design but does not want to have each participant experience all levels of the independent variable.She can accomplish this through what other design option?

The Tukey HSD test helps us determine which means are statistically significantly different from each other in a within-groups ANOVA.

The primary benefit of the within-groups design is that between-groups variability is reduced.

The multiple-group equivalent of a paired-samples t test is the:

When using a one-way within-groups ANOVA, the variability due to individual differences is _, resulting in a _ F statistic.

According to Cohen's conventions, an effect size of 0.062 for a one-way within-groups ANOVA is considered to be:

The one-way within-groups ANOVA has an additional assumption compared to the between-groups ANOVA.Which assumption is unique to the within-groups ANOVA?

The effect size measure for the one-way within-groups ANOVA is Cohen's d.

When conducting the one-way within-groups ANOVA, two F statistics are calculated, but only one is of primary interest.

Each participant experiences all levels of the independent variable in a within-groups design.

Within-groups variability is reduced in the one-way within-groups ANOVA because:

Matched groups require participants who are similar on all the variables that the researcher wants to control.

For the data in the ANOVA source table, what is the effect size? Source SS df MS F Between-groups 13.72 2 6.86 7.831 Subjects 9.01 5 1.802 2.057 Within-groups 8.76 10 0.876 Total 24.49 17

Although the hypothesis test can provide the probability that the levels of the independent variable lead to differences in the dependent variable, it is important to calculate effect size to:

For the data in the source table, calculate the F statistic of interest to researchers. Source SS df MS F Between-groups 12.159 3 4.053 Subjects 6.77 5 1.354 Within-groups 20.4 15 1.360 Total 39.329 23

An Introduction to Statistics and Research Design

Frequency Distributions

Visual Displays of Data

Central Tendency and Variability

Sampling and Probability

The Normal Curve, Standardization and Z Scores

Hypothesis Testing With Z Tests

Confidence Intervals, Effect Size, and Statistical Power

The Single-Sample T Test

The Paired-Samples T Test

The Independent-Samples T Test

One-Way Between-Groups Anova

Two-Way Between-Groups Anova

Correlation

Regression

Chi-Square Tess

Choosing and Reporting Statistics

Filters

Exam 13: One-Way Within-Groups Anova

For the data in the source table, what decision can be made about the hypotheses being tested? Source SS df MS F Between-groups 39.52 2 19.76 Subjects 6.45 5 1.29 Within-groups 19.93 10 1.993 Total 53 17

A researcher wants to take advantage of the strengths of a within-groups design but does not want to have each participant experience all levels of the independent variable.She can accomplish this through what other design option?

The Tukey HSD test helps us determine which means are statistically significantly different from each other in a within-groups ANOVA.

The primary benefit of the within-groups design is that between-groups variability is reduced.

The multiple-group equivalent of a paired-samples t test is the:

When using a one-way within-groups ANOVA, the variability due to individual differences is _____, resulting in a _____ F statistic.

According to Cohen's conventions, an effect size of 0.062 for a one-way within-groups ANOVA is considered to be:

The one-way within-groups ANOVA has an additional assumption compared to the between-groups ANOVA.Which assumption is unique to the within-groups ANOVA?

The effect size measure for the one-way within-groups ANOVA is Cohen's d.

When conducting the one-way within-groups ANOVA, two F statistics are calculated, but only one is of primary interest.

Each participant experiences all levels of the independent variable in a within-groups design.

Within-groups variability is reduced in the one-way within-groups ANOVA because:

Matched groups require participants who are similar on all the variables that the researcher wants to control.

For the data in the ANOVA source table, what is the effect size? Source SS df MS F Between-groups 13.72 2 6.86 7.831 Subjects 9.01 5 1.802 2.057 Within-groups 8.76 10 0.876 Total 24.49 17

Although the hypothesis test can provide the probability that the levels of the independent variable lead to differences in the dependent variable, it is important to calculate effect size to:

For the data in the source table, calculate the F statistic of interest to researchers. Source SS df MS F Between-groups 12.159 3 4.053 Subjects 6.77 5 1.354 Within-groups 20.4 15 1.360 Total 39.329 23

An Introduction to Statistics and Research Design

Frequency Distributions

Visual Displays of Data

Central Tendency and Variability

Sampling and Probability

The Normal Curve, Standardization and Z Scores

Hypothesis Testing With Z Tests

Confidence Intervals, Effect Size, and Statistical Power

The Single-Sample T Test

The Paired-Samples T Test

The Independent-Samples T Test

One-Way Between-Groups Anova

Two-Way Between-Groups Anova

Correlation

Regression

Chi-Square Tess

Choosing and Reporting Statistics

Filters

When using a one-way within-groups ANOVA, the variability due to individual differences is _, resulting in a _ F statistic.