Question 1

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the treatments-by-subjects interaction.

Accepted Answer

A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal 
A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal

Question 2

The SSA × S in a one-factor within-subjects analysis of variance represents.

Accepted Answer

A) variation due to the individual differences among subjects 
B) variation due to the treatments-by-subjects interaction 
C) variation due to the independent variable and treatments-by-subjects interaction 
D) total variation of the scores 
A) variation due to the individual differences among subjects 
B) variation due to the treatments-by-subjects interaction 
C) variation due to the independent variable and treatments-by-subjects interaction 
D) total variation of the scores

Question 3

If the null hypothesis is true for a one-factor within-subjects analysis of variance, then Fobs should be.

Accepted Answer

A) either positive or negative depending on the direction of differences among the means 
B) approximately zero 
C) approximately 1.00 
D) greater than 1.00 
A) either positive or negative depending on the direction of differences among the means 
B) approximately zero 
C) approximately 1.00 
D) greater than 1.00

Question 4

The MSA × S in a one-factor between-subjects analysis of variance represents the variation due to the.

Accepted Answer

A) effect of the independent variable plus treatments-by-subjects interaction 
B) error variation from one treatment to another 
C) individual differences among subjects 
D) total variation of scores 
A) effect of the independent variable plus treatments-by-subjects interaction 
B) error variation from one treatment to another 
C) individual differences among subjects 
D) total variation of scores

Question 5

Suppose 11 participants were tested under four treatment conditions in a one-factor within-subjects design. The numerator of the F statistic for the analysis of variance would have degrees of freedom.

Accepted Answer

A) 3 
B) 10 
C) 4 
D) 43 
A) 3 
B) 10 
C) 4 
D) 43

Question 6

The denominator of the F statistic in a one-factor within-subjects analysis of variance.

Accepted Answer

A) is the same as in a one-factor between-subjects analysis of variance 
B) is the same as in trel 
C) represents the interaction of subjects with the independent variable 
D) reflects individual differences unrelated to the effect of the independent variable 
A) is the same as in a one-factor between-subjects analysis of variance 
B) is the same as in trel 
C) represents the interaction of subjects with the independent variable 
D) reflects individual differences unrelated to the effect of the independent variable

Question 7

A one-factor within-subjects analysis of variance partitions the total variation of scores in an experiment into.

Accepted Answer

A) two sources 
B) three sources 
C) four sources 
D) as many sources as needed based on the amount of total variation 
A) two sources 
B) three sources 
C) four sources 
D) as many sources as needed based on the amount of total variation

Question 8

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the interaction of the independent variable with subjects.

Accepted Answer

A) MSA 
B) MSB 
C) MSS 
D) MSA × S 
A) MSA 
B) MSB 
C) MSS 
D) MSA × S

Question 9

The in a one-factor within-subjects analysis of variance represents the total variation of the scores of the experiment.

Accepted Answer

A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal 
A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal

Question 10

The dfTotal in a one-factor within-subjects analysis of variance are equal to.

Accepted Answer

A) N - 1 
B) nA - 1 
C) a - 1 
D) (a - 1)(nA - 1) 
A) N - 1 
B) nA - 1 
C) a - 1 
D) (a - 1)(nA - 1)

Question 11

If the alternative hypothesis is accepted in a one-factor within-subjects analysis of variance on three levels of the independent variable, then it may be concluded that the .

Accepted Answer

A) treatment means differ by more than sampling error alone 
B) three treatment means were obtained from populations with identical means 
C) treatment means are not equal to the population means 
D) variances of the sample are not equal to the variance of the population 
A) treatment means differ by more than sampling error alone 
B) three treatment means were obtained from populations with identical means 
C) treatment means are not equal to the population means 
D) variances of the sample are not equal to the variance of the population

Question 12

If 30 people were each tested under three treatment conditions in a within-subjects experiment, then the dfTotal would be for the analysis of variance.

Accepted Answer

A) 2 
B) 29 
C) 90 
D) 89 
A) 2 
B) 29 
C) 90 
D) 89

Question 13

The MSA term in a one-factor between-subjects analysis of variance represents variation due to the.

Accepted Answer

A) effect of the independent variable plus error variation 
B) error variation from one treatment to another 
C) individual differences among participants 
D) interaction of subjects with the independent variable 
A) effect of the independent variable plus error variation 
B) error variation from one treatment to another 
C) individual differences among participants 
D) interaction of subjects with the independent variable

Question 14

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the independent variable and error variation.

Accepted Answer

A) MSA 
B) MSB 
C) MSS 
D) MSA × S 
A) MSA 
B) MSB 
C) MSS 
D) MSA × S

Question 15

If the independent variable has no effect in a one-factor within-subjects analysis of variance, then MSA will be MSA × S, and the resulting F statistic will be.

Accepted Answer

A) smaller than; under 1.00 
B) nearly equal to; about 1.00 
C) larger than; over 1.00 
D) smaller than; over 1.00 
A) smaller than; under 1.00 
B) nearly equal to; about 1.00 
C) larger than; over 1.00 
D) smaller than; over 1.00

Question 16

If MSA = 72.00, MSA × S = 12.00, and MSS = 24.00, then Fobs equals in a one-factor within-subjects analysis of variance.

Accepted Answer

A) 2.00 
B) 3.00 
C) 0.17 
D) 6.00 
A) 2.00 
B) 3.00 
C) 0.17 
D) 6.00

Question 17

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the independent variable as well as treatments-by-subjects interaction.

Accepted Answer

A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal 
A) SSA 
B) SSS 
C) SSA × S 
D) SSTotal

Question 18

The situation that presumably exists if the independent variable has an effect is represented by in a one-factor within-subjects analysis of variance.

Accepted Answer

A) H0 
B) H1 
C) MSTotal 
D) SSTotal 
A) H0 
B) H1 
C) MSTotal 
D) SSTotal

Question 19

If the results of a one-factor within-subjects analysis of variance were summarized as F(2, 28) = 2.79, p > .05, then you know that the experiment used subjects and the differences between the treatment condition means were .

Accepted Answer

A) 15; nonsignificant 
B) 15; statistically significant 
C) 29; statistically significant 
D) 29; nonsignificant 
A) 15; nonsignificant 
B) 15; statistically significant 
C) 29; statistically significant 
D) 29; nonsignificant

Question 20

If an experiment using a one-factor within-subjects design has four treatment conditions and uses a total of 12 participants, then the dfS equals.

Accepted Answer

A) 3 
B) 11 
C) 12 
D) 33 
A) 3 
B) 11 
C) 12 
D) 33

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the treatments-by-subjects interaction.

The SSA × S in a one-factor within-subjects analysis of variance represents.

If the null hypothesis is true for a one-factor within-subjects analysis of variance, then Fobs should be.

The MSA × S in a one-factor between-subjects analysis of variance represents the variation due to the.

Suppose 11 participants were tested under four treatment conditions in a one-factor within-subjects design. The numerator of the F statistic for the analysis of variance would have degrees of freedom.

The denominator of the F statistic in a one-factor within-subjects analysis of variance.

A one-factor within-subjects analysis of variance partitions the total variation of scores in an experiment into.

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the interaction of the independent variable with subjects.

The in a one-factor within-subjects analysis of variance represents the total variation of the scores of the experiment.

The dfTotal in a one-factor within-subjects analysis of variance are equal to.

If the alternative hypothesis is accepted in a one-factor within-subjects analysis of variance on three levels of the independent variable, then it may be concluded that the .

If 30 people were each tested under three treatment conditions in a within-subjects experiment, then the dfTotal would be for the analysis of variance.

The MSA term in a one-factor between-subjects analysis of variance represents variation due to the.

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the independent variable and error variation.

If the independent variable has no effect in a one-factor within-subjects analysis of variance, then MSA will be MSA × S, and the resulting F statistic will be.

If MSA = 72.00, MSA × S = 12.00, and MSS = 24.00, then Fobs equals in a one-factor within-subjects analysis of variance.

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the independent variable as well as treatments-by-subjects interaction.

The situation that presumably exists if the independent variable has an effect is represented by in a one-factor within-subjects analysis of variance.

If the results of a one-factor within-subjects analysis of variance were summarized as F(2, 28) = 2.79, p > .05, then you know that the experiment used subjects and the differences between the treatment condition means were .

If an experiment using a one-factor within-subjects design has four treatment conditions and uses a total of 12 participants, then the dfS equals.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters

Exam 12: One-Factor Within-Subjects Analysis of Variance

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the treatments-by-subjects interaction.

The SSA × S in a one-factor within-subjects analysis of variance represents.

If the null hypothesis is true for a one-factor within-subjects analysis of variance, then Fobs should be.

The MSA × S in a one-factor between-subjects analysis of variance represents the variation due to the.

Suppose 11 participants were tested under four treatment conditions in a one-factor within-subjects design. The numerator of the F statistic for the analysis of variance would have degrees of freedom.

The denominator of the F statistic in a one-factor within-subjects analysis of variance.

A one-factor within-subjects analysis of variance partitions the total variation of scores in an experiment into.

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the interaction of the independent variable with subjects.

The in a one-factor within-subjects analysis of variance represents the total variation of the scores of the experiment.

The dfTotal in a one-factor within-subjects analysis of variance are equal to.

If the alternative hypothesis is accepted in a one-factor within-subjects analysis of variance on three levels of the independent variable, then it may be concluded that the .

If 30 people were each tested under three treatment conditions in a within-subjects experiment, then the dfTotal would be for the analysis of variance.

The MSA term in a one-factor between-subjects analysis of variance represents variation due to the.

In a one-factor within-subjects analysis of variance, reflects variation in scores due to the effect of the independent variable and error variation.

If the independent variable has no effect in a one-factor within-subjects analysis of variance, then MSA will be MSA × S, and the resulting F statistic will be.

If MSA = 72.00, MSA × S = 12.00, and MSS = 24.00, then Fobs equals in a one-factor within-subjects analysis of variance.

The in a one-factor within-subjects analysis of variance represents variation due to the effect of the independent variable as well as treatments-by-subjects interaction.

The situation that presumably exists if the independent variable has an effect is represented by in a one-factor within-subjects analysis of variance.

If the results of a one-factor within-subjects analysis of variance were summarized as F(2, 28) = 2.79, p > .05, then you know that the experiment used subjects and the differences between the treatment condition means were .

If an experiment using a one-factor within-subjects design has four treatment conditions and uses a total of 12 participants, then the dfS equals.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters