Understanding Regression Analysis: An Introductory Guide presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output.

Problems and Issues Associated with Regression
Introduction

Almost anyone who has a computer can estimate a linear regression. Regression analysis, for example, can easily be done using a basic spreadsheet program, such as Excel, or by use of any one of a number of statistical packages that are widely available. (Appendix C reproduces the output from estimating equation 1.2 using Excel and four commonly used statistical packages.) The use of such programs is reasonably easy. Although the preceding discussion may seem to suggest that regression analysis is a straightforward exercise without pitfalls, this unfortunately is not the case. Thus, a purely mechanical application of such packages is not appropriate.

Regression analysis, especially hypothesis testing, is based on several ...

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