Statistical Analysis in the Social Sciences / Edition 1

by McKee J McClendon

Overview

Statistical Analysis in the Social Sciences imbeds basic descriptive and inferential statistical concepts within a unified framework: the linear regression model. The regression model is used not only for conducting standard regression analyses but also for other statistical analyses that are ordinarily taught as separate and distinct techniques, such as correlation, difference of means, analysis of variance, and certain nonparametric tests. This extensive use of a single statistical model will increase students' depth of understanding and give them a sense of mastery and self-confidence that they might otherwise fail to achieve in their first statistics course.

Product Details

ISBN-13:	9780534637835
Publisher:	Cengage Learning
Publication date:	09/26/2003
Edition description:	New Edition
Pages:	544
Product dimensions:	7.42(w) x 9.24(h) x 0.75(d)

About the Author

McKee J. McClendon received his Ph.D. in sociology from the University of Kansas in 1972. He is professor emeritus at the University of Akron where he taught statistics, research design, and sociology for 26 years. He is currently a Senior Research Associate, Case Western Reserve University and University Hospitals of Cleveland.

Table of Contents

Preface. 1. Statistics and Social Science. 2. Distributions of Variable Attributes. 3. Central Tendency. 4. Dispersion. 5. Sampling Error. 6. Inferences About the Mean. 7. Associations. 8. Bivariate Regression Analysis. 9. Inferences About the Regression Slope. 10. Multiple Regression. 11. Nominal Independent Variables. 12. Ordinal Dependent Variables. 13. Nominal Dependent Variables. Appendices: Appendix A: Statistical Tables. Appendix B: Answers to Exercises. References. Index.