This work provides a comprehensive and up-to-date introduction to the fundamentals of regression analysis. The Fourth Edition of "Introduction to Linear Regression Analysis" describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. This popular book blends both theory and application to equip the reader with an understanding of the basic principles necessary to apply regression model-building techniques in a wide variety of application environments. It assumes a working knowledge of basic statistics and a familiarity with hypothesis testing and confidence intervals, as well as the normal, t, x2, and F distributions. Illustrating all of the major procedures employed by the contemporary software packages MINITAB[registered], SAS[registered], and S-PLUS[registered], the Fourth Edition begins with a general introduction to regression modeling, including typical applications. A host of technical tools are outlined, such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations.