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Regression Analysis in R: A Comprehensive View for the Social Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Regression Analysis in R: A Comprehensive View for the Social Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

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Regression Analysis in R: A Comprehensive View for the Social Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Regression Analysis in R: A Comprehensive View for the Social Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Category

Statistics

Regression Analysis

R Programming

Author

Jocelyn H. Bolin

Publication

Chapman and Hall/CRC

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Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples.

Key Features:

Full output examples complete with interpretation
Full syntax examples to help teach R code
Appendix explaining basic R functions
Methods for multilevel data that are often included in basic regression texts
End of Chapter Comprehension Exercises

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ISBN-10

036727258X

ISBN-13

978-0367272586

Publisher

Chapman and Hall/CRC

Price

69.95

File Type

PDF

Page No.

180

Jocelyn H. Bolin

Jocelyn H. Bolin

Discover more of the author’s books, see similar authors, read author blogs and more ...

About the Author

Jocelyn E. Bolin is professor in the Department of Educational Psychology at Ball State University, where she teaches courses on introductory and intermediate statistics, multiple regression analysis, and multilevel modeling to graduate students in social science disciplines. She earned a PhD in educational psychology from Indiana University Bloomington. Her research interests include statistical methods for classification and clustering and use of multilevel modeling in the social sciences.

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