Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Introduction -- Principles of statistics -- Introduction to linear regression -- Assessing the regression -- Multiple linear regression -- Indicators, interactions, and transformations -- Nonparametric statistics -- Logistic regression -- Diagnostics for logistic regression -- Poisson regression -- Survival analysis -- Proportional hazards regression -- Review of methods -- Appendix: statistical tables.

This textbook for a second course in basic statistics for undergraduates or first-year graduate students introduces linear regression models and describes other linear models including Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression. Numerous examples drawn from the news and current events with an emphasis on health issues illustrate these concepts. Assuming only a pre-calculus background, the author keeps equations to a minimum and demonstrates all computations using SAS. Most of the programs and output are displayed in a self-contained way, with an emphasis on the interpretation of the output in terms of how it relates to the motivating example. Plenty of exercises conclude every chapter. All of the datasets and SAS programs are available from the book's website, along with other ancillary material.