Handbook of Statistical Analyses using R
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A01=Torsten Hothorn
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Additive Quantile Regression
advanced statistical modeling
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analysis of variance
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Author_Torsten Hothorn
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Bayesian statistics
Brian S. Everitt
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Gee Procedure
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Head Circumference
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Linear Mixed Effect Models
longitudinal data
Lung Cancer Case Control Study
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principal component analysis
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Quantile Regression
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Random Intercept Model
regression
Scatterplot Matrix
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Simple Linear Regression Fit
simultaneous inference
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statistical analyses
Summary Method
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Product details
- ISBN 9781482204582
- Weight: 642g
- Dimensions: 156 x 234mm
- Publication Date: 25 Jun 2014
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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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
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- 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.
Torsten Hothorn, Brian S. Everitt
