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Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.

Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.

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420 CHAPTER 13 | Repeated-Measures Analysis of Variance

13.2 Hypothesis Testing and Effect Size

with the Repeated-Measures ANOVA

LEARNING OBJECTIVES

2. Describe the two-stage structure of the repeated-measures ANOVA and explain what

happens in each stage.

3. Calculate all of the SS, df, and MS values needed for a repeated-measures ANOVA

and explain the relationships among them.

4. Conduct a complete repeated-measures ANOVA and a measure of effect size.

5. Describe how the results of a repeated-measures ANOVA are reported in the

literature and explain how to determine the number of treatments and the number

of participants from the reported df values for the F-ratio.

The overall structure of the repeated-measures ANOVA is shown in Figure 13.2. Note

that the ANOVA can be viewed as a two-stage process. In the first stage, the total variance

is partitioned into two components: between-treatments variance and within-treatments

variance. This stage is identical to the analysis that we conducted for the independentmeasures

design in Chapter 12.

The second stage of the analysis is intended to remove the individual differences from

the denominator of the F-ratio. In the second stage, we begin with the variance within treatments

and then measure and subtract out the between-subject variance, which measures the

size of the individual differences. The remaining variance, often called the residual variance,

or error variance, provides a measure of how much variance is reasonable to expect

Total

variance

Stage 1

Between-treatments

variance

1. Treatment effect

2. Error or chance

(excluding individual

differences)

Within-treatments

variance

1. Individual

differences

2. Other error

Numerator of

F-ratio

Stage 2

FIGURE 13.2

The partitioning

of variance for a

repeated-measures

research study.

Between-subjects

variance

1. Individual

differences

Error

variance

1. Error (excluding

individual

differences)

Denominator of

F-ratio

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