The best-selling introduction to statistics for students in the behavioral and social sciences, the Seventh Edition of STATISTICS FOR THE BEHAVIORAL SCIENCES continues to offer students straightforward instruction, accuracy, built-in learning aids, and real-world examples. Authors Frederick Gravetter and Larry Wallnau help students understand statistical procedures through a conceptual context that explains why the procedure was developed and when it should be used. The authors offer students numerous opportunities to practice statistical techniques through learning checks, examples, demonstrations, and problems. Instructors value the unparalleled ancillary package that accompanies this book, now including JoinInTM on TurningPoint® content for Personal Response System "clickers."

New to the Edition

• The authors have added a new Chapter 17, "Introduction to Regression," which includes new sections on analysis of regression and multiple regression with two predictor variables. Chapter 16, "Correlation," now covers Pearson, Spearman, and point-biserieal correlations as well as the phi coefficient.
• In Chapter 1, "Introduction to Statistics," the authors place more emphasis on data structures and their relationship to statistical techniques and less emphasis on research methodology. They have added examples of the different scales of measurement.
• Chapter 2, "Frequency Distributions," has been edited to emphasize accurate labeling of the axes for frequency distribution graphs.
• Chapter 3, "Central Tendency," includes a new discussion noting that most examples of computing the median are based on continuous variables and acknowledging that some of the conventions involving the median can change if a discrete variable is involved.
• The authors have placed greater emphasis on the definition and concept of variance and standard deviation in Chapter 4, "Variability." In this chapter, they've also expanded coverage of degrees of freedom for sample variance.
• Chapter 5, "z-Scores: Location of Scores and Standardized Distributions," includes a new section demonstrating and explaining examples of problems based on z-scores other than transforming back and forth between X-scores and z-scores. This chapter also has a new section describing how z-scores can be used with sample data, rather than presenting z-scores exclusively in the context of population distributions.
• The discussion of how standard deviation and the sample size combine to determine the value of the standard error has been expanded in Chapter 7, "Probability and Samples: The Distribution of Sample Means."
• Coverage of statistical power has been completely revised in Chapter 8, "Introduction to Hypothesis Testing," including new figures to illustrate the concept, and an additional section to tie together the concepts of effect size and power. The authors have also added a new section discussing the different factors that influence the outcome of a hypothesis test (the size of the mean difference, the sample size, and the variability of the scores).
• In Chapter 9, "Introduction to the t Statistic," the authors have revised the section on Cohen=s d to clarify that they are now using sample values to obtain an estimate of Cohen=s d (which is defined in terms of population parameters). There is also a new discussion of how sample size and sample variance influence the hypothesis.
• Chapter 11, "The t Test for Two Related Samples," includes a new section discussing order effects and time related factors that are potential problems related exclusively to repeated-measures designs.
• Chapter 20, "Statistical Techniques for Ordinal Data," includes a new section on the Friedman test which is an alternative to a repeated-measures analysis of variance for ordinal data.
• Appendix D is new, providing students with general instructions for using SPSS. Specific, step-by-step instructions for each individual procedure using SPPS are provided for students at the end of the chapter in which the procedure is introduced.

Features

• Gravetter and Wallnau are renowned for their excellent sample problems, found at the end of every chapter, which walk students through problems in a variety of ways. This text is also consistently praised by professors and students alike for the friendly, accessible writing style.
• Each chapter begins with an "Overview" and ends with a "Summary," a "Focus on Problem Solving," "Demonstrations," and "Problems" sections to give students the opportunity to assimilate the material and work through sample problems.
• Numerous "Learning Checks" in every chapter challenge students to test their comprehension as they read through the chapter. This feature is also helpful when studying for exams.
• Statistical formulas are presented in both standard mathematical notation and in everyday language, with explanations of how and why formulas are used.
• "In the Literature" sections, which appear in nearly every chapter, demonstrate how statistical results are reported in APA style and explain the notation and jargon used.
• Consistently praised by professors and students alike, summary charts and graphs are used throughout this text. For example, a "Statistics Organizer" at the end of the text provides a decision tree to guides students to appropriate statistical procedures within the text.
• The measurement of effect size is included throughout the inferential statistics chapters (8, 9, 10, 11, 13, 14, 15, 16, and 18).

Part I. INTRODUCTION AND DESCRIPTIVE STATISTICS.

1. Introduction to Statistics.
2. Frequency Distributions.
3. Central Tendency.
4. Variability.

Part II. FOUNDATIONS OF INFERENTIAL STATISTICS.

5. z-Scores: Location of Scores and Standardized Distributions.
6. Probability.
7. Probability and Samples: The Distribution of Sample Means.

Part III. INFERENCES ABOUT MEANS AND MEAN DIFFERENCES.

8. Introduction to Hypothesis Testing.
9. Introduction to the t-Statistic.
10. The t-Test for Two Independent Samples.
11. The t-Test for Two Related Samples.
12. Estimation.
13. Introduction to Analysis of Variance.
14. Repeated-Measures Analysis of Variance (ANOVA).
15. Two-Factor Analysis of Variance (Independent Measures).

Part IV. CORRELATIONS AND NONPARAMETRIC TESTS.

16. Correlation.
17. Introduction to Regression.
18. The Chi-Square Statistic: Tests for Goodness of Fit and Independence.
19. The Binomial Test.
20. Statistical Techniques for Ordinal Data: Mann-Whitney, Wilcoxon, Kruskal-Wallis, and Friedman Tests.

Appendix A: Basic Mathematics Review.
Appendix B: Statistical Tables.
Appendix C: Solutions for End-of-Chapter Problems.
Appendix D: General Insturctions for Using SPSS.
Statistics Organizer. References.
Index.