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.
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.
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.