Handbook of Statistical Analyses using R

Regular price €80.99
A01=Brian S. Everitt
A01=Torsten Hothorn
Ab Ilit
Additive Quantile Regression
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Age Group_Uncategorized
analysis of variance
Author_Brian S. Everitt
Author_Torsten Hothorn
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Brian S. Everitt
Category1=Non-Fiction
Category=PBT
Category=UMX
Cloud Seeding
Conditional Quantiles
COP=United States
Cumulative Distribution Function
Data Set
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eq_computing
eq_isMigrated=2
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Gee Procedure
graphical displays
Head Circumference
Language_English
Linear Mixed Effect Models
longitudinal data
Lung Cancer Case Control Study
Median Regression Model
Min 1Q Median 3Q Max
Missing Values
Multiple Linear Regression
Multiply Imputed Data
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NA NA Non
Pa Rti
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Proportional Odds Model
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Quantile Regression
R
Random Intercept Model
regression
Scatterplot Matrix
Scatterplot Smoothers
Simple Linear Regression Fit
simultaneous inference
softlaunch
statistical analyses
Summary Method

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

  • 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