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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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SUMMARY 355

and the other group receiving treatment 2 followed by treatment 1. The goal of counterbalancing

is to distribute any outside effects evenly over the two treatments. For example,

if practice effects are a problem, then half of the participants will gain experience in treatment

1, which then helps their performance in treatment 2. However, the other half will

gain experience in treatment 2, which helps their performance in treatment 1. Thus, prior

experience helps the two treatments equally.

Finally, if there is reason to expect strong time-related effects or strong order effects,

your best strategy is not to use a repeated-measures design. Instead, use independentmeasures

(or a matched-subjects design) so that each individual participates in only one

treatment and is measured only one time.

LEARNING CHECK

1. An advantage of a repeated-measured design (compared to an independent-measures

design) is that it reduces the contribution of error variability due to ______.

a. M D

b. degrees of freedom

c. the effect of the treatment

d. individual differences

2. Compared to a repeated-measures design, which of the following is an advantage of

an independent-measures research design?

a. It usually requires fewer participants.

b. It eliminates the concern that performance in one treatment condition may be

influenced by experience in the other treatment condition.

c. It eliminates the concern that the participants in one treatment may be smarter

than those in the other treatment.

d. It tends to have a smaller variance and a smaller standard error.

3. For which of the following situations would a repeated-measures design have the

maximum advantage over an independent-measures design?

a. when many subjects are available and individual differences are small

b. when very few subjects are available and individual differences are small

c. when many subjects are available and individual differences are large

d. when very few subjects are available and individual differences are large

ANSWERS

1. D, 2. B, 3. D

SUMMARY

1. In a related-samples research study, the individuals

in one treatment condition are directly related,

one-to-one, with the individuals in the other treatment

condition(s). The most common related-samples study

is a repeated-measures design, in which the same

sample of individuals is tested in all of the treatment

conditions. This design literally repeats measurements

on the same subjects. An alternative is a matchedsubjects

design, in which the individuals in one sample

are matched one-to-one with individuals in another

sample. The matching is based on a variable relevant

to the study.

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