Название: Regression Analysis By Example Using R, 6th Edition
Автор: Ali S. Hadi, Samprit Chatterjee
Издательство: Wiley
Год: 2024
Страниц: 483
Язык: английский
Формат: pdf (true)
Размер: 26.8 MB

A straightforward and concise discussion of the essentials of regression analysis.

In the newly revised sixth edition of Regression Analysis By Example Using R, distinguished statistician Dr Ali S. Hadi delivers an expanded and thoroughly updated discussion of exploratory data analysis using regression analysis in R. The book provides in-depth treatments of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression.

The author clearly demonstrates effective methods of regression analysis with examples that contain the types of data irregularities commonly encountered in the real world. This newest edition also offers a brand-new, easy to read chapter on the freely available statistical software package R.

R is a universal language specially suited for statistical computing and graphics, which makes it of interest to researchers and practitioners in Mathematics, Statistics, and Data Science fields. R is also a collection of programs (called functions), which are organized in different but specialized packages (or libraries). These packages are written by professional developers who provide comprehensive collection of help pages that explains every element in R.

Example of packages are stats for statistical calculations and random number generation, DescTools for descriptive statistics, olsrr for regression models, and nlme for linear and nonlinear mixed effects models. Examples of functions include lm() for fitting linear models and glm for generalized linear models. R is an open-source and open-ended software, where continual downloads and updates are made available all for free. If you do not find the already-made programs that you need, you can write your own programs in R.

R is compatible with several platforms including Windows, Macintosh, UNIX, and Linux. There are some differences among these platforms, but fortunately they are not a lot. In this book we use the Windows platform simply because we are Windows users.

Readers will also find:

Reorganized, expanded, and upgraded exercises at the end of each chapter with an emphasis on data analysis
Updated data sets and examples throughout the book
Complimentary access to a companion website that provides data sets in xlsx, csv, and txt format

Perfect for upper-level undergraduate or beginning graduate students in statistics, mathematics, biostatistics, and computer science programs, Regression Analysis By Example Using R will also benefit readers who need a reference for quick updates on regression methods and applications.






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