谢宇所著的《回归分析(修订版)》源于作者多年在密歇根大学教授回归 分析的课程讲义，从基本的统计概念讲起，对线性回归分析的基本假定、回 归中的统计推论和回归诊断做了详尽的介绍，同时还涵盖了很多在社会科学 中对实际研究 有用的内容，包括虚拟变量、交互作用、辅助回归、多项 式回归、样条函数回归和阶跃函数回归等。此外，《回归分析(修订版)》还 涉及通径分析、纵贯数据模型、多层线性模型和logit模型等方面的内容。

This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

《回归分析》源于作者多年在密歇根大学教授回归分析的课程讲义，从基本的统计概念讲起，对线性回归分析的基本假定、回归中的统计推论和回归诊断做了详尽的介绍，同时还涵盖了很多在社会科学中对实际研究非常有用的内容，包括虚拟变量、交互作用、辅助回归、多项式回归、样条函数回归和阶跃函数回归等。此外，《回归分析》还涉及通径分析、纵贯数据模型、多层线性模型和Iogit模型等方面的内容。