Overview
- Compares a number of new real data sets that enable students to learn how regression can be used in real life
- Provides R code used in each example in the text along with the SAS-code and STATA-code to produce the equivalent output
- Complete details provided for each example
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Reviews
“This book fills an important niche in the regression textbook by providing a data-centered approach strong on graphics. …I am particularly interested in teaching regression to undergraduates, and I used this book one term in an introduction to applied regression course. …It is a book I will use again. …Graduate students in particular will find the balance between applications and theory useful, and the minimal amount of formulae used means the book should be useful for students from a variety of disciplines. The well-motivated homework problems are interesting and sufficiently complex that students at all levels will be able to learn something from them.” (Journal of Statistical Software, March 2010, Vo. 33, Book Review 3)
Simon Sheather, A Modern Approach to Regression With R 978-0-387-09607-0
“The author states that this book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. The primary focus is on examining statistical and graphical methods for assessing whether or not the model upon which one desires to draw inferences is valid. … the examples…will have appeal to the students due to the variety of the techniques motivated by the datasets. The author has included numerous graphs and descriptions with associated flow charts to assist the student in ’visualizing’ the process one should take when modeling data using regression models. I found that the book was …very readable and that the graphics were …useful in the analysis of the problem under consideration. The book is also the ’right size’ with enough but not too much content. Personally, I was pleased not to see the voluminous R code that ’litters’ many of the books that are ‘with R.’ I was also pleased that some of the characteristic R output has been minimized and reformatted to improve the appearance of the text.…One of the aspects I found most appealing is that which is not found in the book. The supplementary material given on the author’s webpage is potentially very useful. The R code that was used to create the graphs and output in the book is provided in a separate document. This supplement will be very useful to the student who is learning R. In addition, there are similar documents that use SAS and STATA. I have found that having code to address a specific statistical problem is a very effective way for a student to learn a statistical software package. The author’s supplementary material using all three packages will provide an effective means for a student to learn multiple software packages without having to spend valuable classroom time and instructor supervision.” (The American Statistician, August 2010, Vol. 64, No. 3)
Authors and Affiliations
Bibliographic Information
Book Title: A Modern Approach to Regression with R
Authors: Simon Sheather
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-0-387-09608-7
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2009
Hardcover ISBN: 978-0-387-09607-0Published: 11 March 2009
Softcover ISBN: 978-1-4419-1872-7Published: 29 November 2010
eBook ISBN: 978-0-387-09608-7Published: 27 February 2009
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XIV, 393
Topics: Probability Theory and Stochastic Processes, Econometrics, Statistical Theory and Methods