<p/><br></br><p><b> About the Book </b></p></br></br><strong>An R Companion to Applied Regression </strong>is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The <strong>Third Edition </strong>includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the <em>car</em> and <em>effects</em> packages for R for this new edition, and include coverage of RStudio and R Markdown.<p/><br></br><p><b> Book Synopsis </b></p></br></br><strong>An R Companion to Applied Regression </strong>is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The <strong>Third Edition </strong>includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the <em>car</em> and <em>effects</em> packages for R for this new edition, and include coverage of RStudio and R Markdown.<p/><br></br><p><b> Review Quotes </b></p></br></br><br><strong>An R Companion to Applied Regression </strong>continues to provide the most comprehensive and user-friendly guide to estimating, interpreting, and presenting results from regression models in R. </p>--Christopher Hare<br><br>This is an impressive update to a book I have long admired. The authors have brought the description of how to do data analysis and plots of Applied Regression related data to a modern and more comprehensive level.--Michael Friendly<br><br>This is the best book I've read for teaching the modern practice of regression. By going deeply into both R and applied regression, it manages to use each topic to motivate and illustrate the other. The whole is much greater than sum of the parts because each thread so effectively reinforces the other. There are many nice surprises in this new edition. R Studio and markdown are used to encourage a reproducible workflow. There's an excellent and accessible chapter on mixed and longitudinal data that expands the reach of regression methods to the much more complex data structures typical of current practice. Like its predecessors, this edition is a model of clear, thoughtful exposition. It's an outstanding contribution to the teaching and practice of regression.--Georges Monette<br>
Cheapest price in the interval: 85 on November 6, 2021
Most expensive price in the interval: 85 on February 4, 2022
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