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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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SECTION 12.1 | Introduction (An Overview of Analysis of Variance) 371

If you compute the variance for the three numbers in each set, then the variance is

s 2 = 58.33 for set 1 and the variance is s 2 = 2.33 for set 2 is. Notice that the two variances

provide an accurate representation of the size of the differences. In set 1 there are relatively

large differences between sample means and the variance is relatively large. In set 2 the

mean differences are small and the variance is small.

Thus, we can use variance to measure sample mean differences when there are two or

more samples. The test statistic for ANOVA uses this fact to compute an F-ratio with the

following structure:

variance sdifferencesd between sample means

F 5

variance sdifferencesd expected with no treatment effect

Note that the F-ratio has the same basic structure as the t statistic but is based on

variance instead of sample mean difference. The variance in the numerator of the F-ratio

provides a single number that measures the differences among all of the sample means.

The variance in the denominator of the F-ratio, like the standard error in the denominator

of the t statistic, measures the mean differences that would be expected if there is no

treatment effect. Thus, the t statistic and the F-ratio provide the same basic information.

In each case, a large value for the test statistic provides evidence that the sample mean differences

(numerator) are larger than would be expected if there were no treatment effects

(denominator).

LEARNING CHECK

1. Which of the following is the correct description for a research study comparing

problem-solving scores obtained for 3 different age groups of children?

a. single-factor design

b. two-factor design

c. three-factor design

d. factorial design

2. ANOVA is necessary to evaluate mean differences among three or more treatments,

in order to ____________________ .

a. minimize risk of Type I error

b. maximize risk of Type I error

c. minimize risk of Type II error

d. maximize risk of Type II error

3. The numerator of the F-ratio measures the size of the sample mean differences.

How is this number obtained, especially when there are more than two sample

means?

a. by computing the sum of the sample mean differences

b. by computing the average of the sample mean differences

c. by the largest of the sample mean differences.

d. by computing the variance for the sample means

ANSWERS

1. A, 2. A, 3. D

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