Gravetter and Wallnau's proven best-seller offers the straightforward instruction, accuracy, built-in learning aids, and wealth of real-world examples that professors AND students have come to appreciate. The authors integrate applications to ensure that even students with a weak background in mathematics can achieve mastery of statistical concepts. They skillfully demonstrate that having an understanding of statistical procedures will help them not only understand published findings, but also become savvy consumers of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support instructors with class preparation and testing.
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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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