This book covers introductory statistical methods for the social and behavioral sciences from a linear models perspective. The author argues that the research methodologies found in the social sciences and human studies are not inferior to those found in the physical sciences. He therefore provides methodologies that can be used in almost any field. The diversity of examples in this book helps students to broaden their scope and understanding of statistics. This book is a highly appropriate text for upper division undergraduate courses in beginning statistics or graduate level courses in the social and behavioral sciences, including education. Contents: Preface; Acknowledgments; Introduction; Basic Ideas in Measurement; The Use of Symbols in Statistics; Measures of Central Tendency and Variability; Grouping and Graphing of Data; The Normal Curve; Transformed Scores; Linear Regression and Prediction; Correlation; An Introduction to Computer Usuage; Probability And The Binomial Distributrion; Sampling; Multiple Regression and Multiple Correlation; The Logic of Statistical Inference; The t Test for Meand; Additional Considerations of the t Test; Analysis of Variance of Regression; Multiple Comparisons in a Regression Approach; The Chi-Square Test for Categorical Data; Stepwise and Setwise Regression Analysis; Appendix; Answers to Exercises; References; Index; About the Author.