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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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10 CHAPTER 1 | Introduction to Statistics

5. IQ tests are standardized so that the average score is 100 for the entire group of

people who take the test each year. However, if you selected a group of 20 people

who took the test and computed their average IQ score you probably would not get

100. What statistical concept explains the difference between your mean and the

mean for the entire group?

a. statistical error

b. inferential error

c. descriptive error

d. sampling error

ANSWERS

1. B, 2. C, 3. C, 4. B, 5. D

1.2 Data Structures, Research Methods, and Statistics

LEARNING OBJECTIVES

4. Differentiate correlational, experimental, and nonexperimental research and describe

the data structures associated with each.

5. Define independent, dependent, and quasi-independent variables and recognize

examples of each.

■ Individual Variables: Descriptive Research

Some research studies are conducted simply to describe individual variables as they exist

naturally. For example, a college official may conduct a survey to describe the eating, sleeping,

and study habits of a group of college students. When the results consist of numerical

scores, such as the number of hours spent studying each day, they are typically described

by the statistical techniques that are presented in Chapters 3 and 4. Non-numerical scores

are typically described by computing the proportion or percentage in each category. For

example, a recent newspaper article reported that 34.9% of Americans are obese, which is

roughly 35 pounds over a healthy weight.

■ Relationships Between Variables

Most research, however, is intended to examine relationships between two or more variables.

For example, is there a relationship between the amount of violence in the video

games played by children and the amount of aggressive behavior they display? Is there a

relationship between the quality of breakfast and academic performance for elementary

school children? Is there a relationship between the number of hours of sleep and grade

point average for college students? To establish the existence of a relationship, researchers

must make observations—that is, measurements of the two variables. The resulting

measurements can be classified into two distinct data structures that also help to classify

different research methods and different statistical techniques. In the following section we

identify and discuss these two data structures.

I. One Group with Two Variables Measured for Each Individual: The Correlational

Method One method for examining the relationship between variables is to

observe the two variables as they exist naturally for a set of individuals. That is, simply

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