Statistics for the Behavioral Sciences 10/e AE【含Access Code,刮除不受退】

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.

The late Frederick J Gravetter was Professor Emeritus of Psychology at The College at Brockport, State University of New York. While teaching at Brockport, Dr. Gravetter specialized in statistics, experimental design, and cognitive psychology. He received his bachelor’s degree in mathematics from M.I.T. and his Ph.D. in psychology from Duke University. In addition to publishing several research articles, Dr. Gravetter co-authored Statistics for the Behavioral Sciences and Essentials of Statistics for the Behavioral Sciences.

Larry B. Wallnau is Professor Emeritus of Psychology at The College at Brockport, State University of New York. While teaching at Brockport, he published numerous research articles in biopsychology and provided editorial consultation for journals in his field. He has taught statistics, animal behavior, biopsychology, psychopharmacology and introductory psychology. With Dr. Frederick J Gravetter, he co-authored all previous editions of STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its 10th edition. Dr. Wallnau received his bachelor's degree from the University of New Haven and his Ph.D. in psychology from the State University of New York at Albany. In his leisure time, he is an avid runner with his canine companion, Gracie.

●In-text learning aids give students many opportunities to master the material by practicing working through problems. A Focus on Problem Solving section in each chapter offers practical tips on deciding which formulas to use and cautions for avoiding common errors.
●In the Literature sections, which appear in nearly every chapter, demonstrate how statistical results (e.g., for the mean and the standard deviation, t tests, and independent-measures tests) are reported in APA style and explain the notation and jargon used.
●The book's conceptual context helps make learning statistics as simple as possible for students who may be intimidated by the subject. Statistical formulas are presented in both standard mathematical notation and in everyday language, with explanations of how and why formulas are used.
●An appendix contains a general introduction to IBM SPSS®. In addition, at the end of each chapter for which an SPSS analysis is feasible, a step-by-step set of instructions describes how to enter data and run the analysis, and presents an example of the output.
●This edition's excellent problems, which walk students step-by-step through procedures in a variety of ways, reflect the straightforward writing for which Gravetter and Wallnau are renowned. Each chapter ends with 20 to 30 problems.

1. Introduction to Statistics.
2. Frequency Distributions.
3. Central Tendency.
4. Variability.
5. z-Scores: Location of Scores and Standardized Distributions.
6. Probability.
7. Probability and Samples: The Distribution of Sample Means.
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. Introduction to Analysis of Variance.
13. Repeated-Measures Analysis of Variance (ANOVA).
14. Two-Factor Analysis of Variance (Independent Measures).
15. Correlation.
16. Introduction to Regression.
17. The Chi-Square Statistic: Tests for Goodness of Fit and Independence.
18. The Binomial Test.