9781138469792-1138469793-A Handbook of Statistical Analyses using R

A Handbook of Statistical Analyses using R

ISBN-13: 9781138469792
ISBN-10: 1138469793
Edition: 3
Author: Torsten Hothorn, Brian S. Everitt
Publication date: 2017
Publisher: Chapman and Hall/CRC
Format: Hardcover 304 pages
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Book details

ISBN-13: 9781138469792
ISBN-10: 1138469793
Edition: 3
Author: Torsten Hothorn, Brian S. Everitt
Publication date: 2017
Publisher: Chapman and Hall/CRC
Format: Hardcover 304 pages

Summary

A Handbook of Statistical Analyses using R (ISBN-13: 9781138469792 and ISBN-10: 1138469793), written by authors Torsten Hothorn, Brian S. Everitt, was published by Chapman and Hall/CRC in 2017. With an overall rating of 4.4 stars, it's a notable title among other Cloud Computing (Networking & Cloud Computing, Mathematical & Statistical, Software, Programming Languages) books. You can easily purchase or rent A Handbook of Statistical Analyses using R (Hardcover) from BooksRun, along with many other new and used Cloud Computing books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.32.

Description

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis. New to the Third Edition Three new chapters on quantile regression, missing values, and Bayesian inference Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables Additional exercises More detailed explanations of R code New section in each chapter summarizing the results of the analyses Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses Whether you‘re a data analyst, scientist, or student, this handbook shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.

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