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Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts Statistical Methods for the Social Sciences introduces statistical methods to students majoring in social science disciplines. With an emphasis on concepts and applications, this book assumes no previous knowledge of statistics and only a minimal mathematical background. It contains sufficient material for a two-semester course. The 5th Edition uses examples and exercises with a variety of "real data.ö It includes more illustrations of statistical software for computations and takes advantage of the outstanding applets to explain key concepts, such as sampling distributions and conducting basic data analyses. It continues to downplay mathematics-often a stumbling block for students-while avoiding reliance on an overly simplistic recipe-based approach to statistics.



Preface

Acknowledgments

Introduction
Sampling and Measurement
Descriptive Statistics
Probability Distributions
Statistical Inference: Estimation
Statistical Inference: Significance Tests
Comparison of Two Groups
Analyzing Association between Categorical Variables
Linear Regression and Correlation
Introduction to Multivariate Relationships
Multiple Regression and Correlation
Regression with Categorical Predictors: Analysis of Variance Methods
Multiple Regression with Quantitative and Categorical Predictors
Model Building with Multiple Regression
Logistical Regression: Modeling Categorical Responses
Appendix: R, Stata, SPSS, and SAS for Statistical Analyses

Answers to Select Odd-Numbered Exercises

Bibliography

Credits

Index