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Applied Regression Modeling, by Iain Pardoe
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Praise for the First Edition
"The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician
Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications.
The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling.
In addition, the Second Edition features clarification and expansion of challenging topics, such as:
- Transformations, indicator variables, and interaction
- Testing model assumptions
- Nonconstant variance
- Autocorrelation
- Variable selection methods
- Model building and graphical interpretation
Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos.
With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
- Sales Rank: #427084 in eBooks
- Published on: 2013-01-07
- Released on: 2013-01-07
- Format: Kindle eBook
Review
“With an intuitive approach that is not heavy on mathematical detail, the book is can be used for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.”� (Zentralblatt MATH, 1 October 2013)
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From the Back Cover
Praise for the First Edition
"The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician
Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications.
The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling.
In addition, the Second Edition features clarification and expansion of challenging topics, such as:
- Transformations, indicator variables, and interaction
- Testing model assumptions
- Nonconstant variance
- Autocorrelation
- Variable selection methods
- Model building and graphical interpretation
Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos.
With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
About the Author
IAIN PARDOE, PhD, is an independent consultant and also serves on the faculty of mathematics and statistics at Thompson Rivers University, Canada. He has published extensively in his areas of research interest, which include Bayesian analysis, multilevel modeling, graphical methods, and statistics education.
Most helpful customer reviews
4 of 4 people found the following review helpful.
Outstanding!
By Ashvaghosha
This book is extremely well produced. The combination of thoughtful examples, excellent real-world datasets, good exercise problems with hints to help you get started and guidance for using the most common software packages (including open-source R) make this a very thorough, self-contained introduction to linear regression. There is a strong emphasis on understanding, application and interpretation. The writing style is crystal clear. It is an ideal tool for independent learning - just follow along with the text using the datasets available from the website & your favorite statistical analysis software. This is the best elementary, practical introduction to linear regression that I have come across, well worth the investment!
4 of 4 people found the following review helpful.
excellent textbook
By vinvin
Applied Regression Modeling by Iain Pardoe is a very well written textbook about basic linear regression analysis. It is excellent for self study. The language is plain and simple. The approach is entertaining. And the math is easy to understand. You almost feel like you are in the classroom listening to a live lecture. The accompanying website is very informative. Especially the 5 min video clips and computer help are very useful. I recommend this book for anyone interested in learning the basics of regression. It is an excellent practical guide for those at beginner and intermediate level.
0 of 3 people found the following review helpful.
One Star
By Amazon Customer
no real page numbers!
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