Although many people have PCs with software capable of performing regression techniques, only a few know how to capitalize on the flexibility and wide application of regression analysis. This book shows readers how to get the most from regression by providing a friendly, non-technical introduction to the subject. Accessible to anyone with only an introductory statistics background, the book begins with the simplest, two-variable linear model and gradually builds towards models of more complexity, such as multivariate regression. Kahane uses three engaging examples to illustrate regression concepts. These examples show the creative way in which regression analysis can be used to determine why some professional sports players earn higher salaries than others, the factors that affect voting patterns in presidential elections, and how to determine the factors that explain differences in abortion rates. Data for these examples are provided in an Appendix so that readers can have tangible, hands-on experience in performing linear regression analysis.
"synopsis" may belong to another edition of this title.
"This book makes a breakthrough in terms of teaching regression analysis through real world examples that progress in complexity."
Author: William C. Birdsall"Regression Basics fills an important place in the statistical textbook. . . it explains many complicated statistical concepts in a very straightforward and non-jargon-filled manner. A very refreshing and quite enjoyable read."
Author: Lynn Sorsoli". . . does a great job explaining technical concepts in a straightforward and non-technical manner. . . can give students from any discipline a head start to understanding the technical details of regression procedures . . . "
Author: Jerry Welkenhuysen-Gybels"About this title" may belong to another edition of this title.
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