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 ...
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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.
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Add this copy of Regression Basics to cart. $7.75, very good condition, Sold by ThriftBooks-Baltimore rated 4.0 out of 5 stars, ships from Halethorpe, MD, UNITED STATES, published 2007 by Sage Publications, Inc.
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