Applied Linear Regression

"Applied Linear Regression" by Sanford Weisberg is a comprehensive guide to understanding and implementing linear regression analysis in real-world scenarios. Weisberg is a professor of statistics at the University of Minnesota, and his vast experience in the field is evident in this book. It is one of the best books on linear regression.

The book begins by providing a solid foundation in the basics of linear regression, including assumptions, estimation, and inference. From there, Weisberg delves into more advanced topics, such as model selection, diagnostics, and regression with categorical predictors.

One of the unique features of this book is its focus on practical applications of linear regression. Weisberg includes numerous examples from fields such as economics, psychology, and engineering, demonstrating how regression can be used to answer important questions in these domains.

The book also includes practical advice for working with real data, such as how to handle missing values and outliers. Weisberg emphasizes the importance of exploratory data analysis and provides guidance on how to use graphical techniques to understand the relationships between variables.

Throughout the book, Weisberg uses clear and accessible language, making even complex topics easy to understand. The book is also filled with helpful diagrams and illustrations, making it a valuable resource for both beginners and experienced practitioners.

Overall, "Applied Linear Regression" is an essential guide for anyone looking to gain a deep understanding of linear regression and its practical applications. Whether you're a student, researcher, or practitioner, this book is sure to become a go-to reference for years to come.

Author: Kjell Johnson ,Max Kuhn

Link to buy: https://www.amazon.com/dp/1461468485

Ratings: 4.6 out of 5 stars (from 297 reviews)

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