This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models using SAS.
This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models using SAS.
Dr Daniel Zelterman is Professor of Epidemiology and Public Health in the Division of Biostatistics at Yale University. His application areas include work in genetics, HIV, and cancer. Before moving to Yale in 1995, he was on the faculty of the University of Minnesota and at the State University of New York at Albany. He is an elected Fellow of the American Statistical Association. He serves as associate editor of Biometrics and other statistical journals. He is the author of Models for Discrete Data (1999), Advanced Log-Linear Models Using SAS (2002), Discrete Distributions: Application in the Health Sciences (2004), and Models for Discrete Data, 2nd edition (2006).
Inhaltsangabe
1. Introduction 2. Principles of statistics 3. Introduction to linear regression 4. Assessing the regression 5. Multiple linear regression 6. Indicators, interactions, and transformations 7. Nonparametric statistics 8. Logistic regression 9. Diagnostics for logistic regression 10. Poisson regression 11. Survival analysis 12. Proportional hazards regression 13. Review of methods Appendix: statistical tables.
