Master statistics with STATISTICS FOR THE BEHAVIORAL SCIENCES! With straightforward instruction, built-in learning aids, and real world examples, this psychology text provides you with the tools you need to succeed. You will have numerous opportunities to practice statistical techniques through learning checks, examples, demonstrations, and problems. Exam preparation is made easy with a student companion website that provides tutorials, crossword puzzles, flashcards, learning objectives, and more!
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Frederick J Gravetter is Professor Emeritus of Psychology at The College at Brockport, State University of New York. While teaching at Brockport, he specialized in statistics, research design, and cognitive psychology. Dr. Gravetter 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 is co-author of the best-selling STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition, ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, 9th Edition, and RESEARCH METHODS FOR THE BEHAVIORAL SCIENCES, 5th Edition. Larry B. Wallnau is Professor Emeritus of Psychology at The College at Brockport, State University of New York. The recipient of grants and awards in both research and teaching, Dr. Wallnau has published numerous research articles primarily on the effect of psychotropic drugs. With Frederick J Gravetter, he has co-authored previous editions of STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its tenth edition, and ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, now in its ninth edition.
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. 8. Introduction to Hypothesis Testing. Part III: USING t STATISTICS FOR INFERENCES ABOUT POPULATION MEANS AND MEAN DIFFERENCES. 9. Introduction to the t Statistics. 10. The t Test for Two Independent Samples. 11. The t Test for Two Related Samples. Part IV: ANALYSIS OF VARIANCE: TESTS FOR DIFFERENCES AMONG TWO OR MORE POPULATION MEANS. 12. Introduction to Analysis of Variance. 13. Repeated-Measures Analysis of Variance (ANOVA). 14. Two-Factor Analysis of Variance (Independent Measures). Part V: CORRELATIONS AND NON-PARAMETRIC TESTS. 15. Correlation. 16. Introduction to Regression. 17. The Chi-Square Statistic: Tests for Goodness of Fit and Independence. 18. The Binomial Test. 19. How to Decide Which Statistics Technique Is Appropriate for a Given Data Set.
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