An R Companion to Applied Regression

This book PDF is perfect for those who love Social Science genre, written by John Fox and published by SAGE Publications which was released on 27 September 2018 with total hardcover pages 608. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related An R Companion to Applied Regression books below.

An R Companion to Applied Regression
Author : John Fox
File Size : 47,6 Mb
Publisher : SAGE Publications
Language : English
Release Date : 27 September 2018
ISBN : 9781544336480
Pages : 608 pages
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An R Companion to Applied Regression by John Fox Book PDF Summary

An R Companion to Applied Regression 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 Third Edition 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 car and effects packages for R for this new edition, and include coverage of RStudio and R Markdown.

An R Companion to Applied Regression

An R Companion to Applied Regression 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

Get Book
An R Companion to Applied Regression

An R Companion to Applied Regression 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

Get Book
An R Companion to Applied Regression

This book aims to provide a broad introduction to the R statistical environment in the context of applied regression analysis, which is typically studied by social scientists and others in a second course in applied statistics.

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An R Companion to Applied Regression

This is a broad introduction to the R statistical computing environment in the context of applied regression analysis. It is a thoroughly updated edition of John Fox's bestselling text An R and S-Plus Companion to Applied Regression (SAGE, 2002). The Second Edition is intended as a companion to any course on

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An R and S Plus Companion to Applied Regression

"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all

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Applied Regression Analysis and Generalized Linear Models

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes

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Applied Regression Modeling

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

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An R Companion to Linear Statistical Models

Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis

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