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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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252 CHAPTER 8 | Introduction to Hypothesis Testing

Cohen’s d measures the

distance between two

means and is typically

reported as a positive

number even when the

formula produces a

negative value.

representative of the population mean and provides the best measure of the treatment

effect. Thus, the actual calculations are really estimating the value of Cohen’s d as follows:

estimated Cohen’s d 5

mean difference

standard deviation 5 M 2m treatment no treatment

s

(8.2)

The standard deviation is included in the calculation to standardize the size of the mean difference

in much the same way that z-scores standardize locations in a distribution. For example,

a 15-point mean difference can be a relatively large treatment effect or a relatively small

effect depending on the size of the standard deviation. This phenomenon is demonstrated in

Figure 8.9. The top portion of the figure (part a) shows the results of a treatment that produces

a 15-point mean difference in SAT scores; before treatment, the average SAT score is μ =

500, and after treatment the average is 515. Notice that the standard deviation for SAT scores is

σ = 100, so the 15-point difference appears to be small. For this example, Cohen’s d is

Cohen’s d 5

mean difference

standard deviation 5 15

100 5 0.15

(a)

Distribution of SAT

scores before treatment

m 5 500 and s 5 100

d 5 0.15

Distribution of SAT

scores after treatment

m 5 515 and s 5 100

s 5 100

m 5 500

(b)

Distribution of IQ

scores before treatment

m 5 100 and s 5 15

d 5 1.00

Distribution of IQ

scores after treatment

m 5 115 and s 5 15

s 5 15

m 5 100

FIGURE 8.9

The appearance of a 15-point treatment effect in two different situations. In part (a), the standard deviation is σ = 100 and

the 15-point effect is relatively small. In part (b), the standard deviation is σ = 15 and the 15-point effect is relatively large.

Cohen’s d uses the standard deviation to help measure effect size.

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