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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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498 CHAPTER 15 | Correlation

60

Number of serious crimes

50

40

30

20

FIGURE 15.5

Hypothetical data showing the

logical relationship between

the number of churches and

the number of serious crimes

for a sample of U.S. cities.

10

0 10 20

30 40 50 60 70

Number of churches

■ Correlation and Restricted Range

Whenever a correlation is computed from scores that do not represent the full range of possible

values, you should be cautious in interpreting the correlation. Suppose, for example,

you are interested in the relationship between IQ and creativity. If you select a sample of

your fellow college students, your data probably will represent only a limited range of IQ

scores (most likely from 110–130). The correlation within this restricted range could be

completely different from the correlation that would be obtained from a full range of IQ

scores. For example, Figure 15.6 shows a strong positive relationship between X and Y

when the entire range of scores is considered. However, this relationship is obscured when

the data are limited to a restricted range.

To be safe, you should not generalize any correlation beyond the range of data represented

in the sample. For a correlation to provide an accurate description for the general

population, there should be a wide range of X and Y values in the data.

FIGURE 15.6

In this example, the full range of X and

Y values shows a strong, positive correlation,

but the restricted range of scores

produces a correlation near zero.

Y values

X values

X values restricted

to a limited range

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