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Full 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.
Contents
An Introduction to R. Data Analysis Using Graphical Displays. Simple Inference. Conditional Inference. Analysis of Variance. Simple and Multiple Linear Regression. Logistic Regression and Generalized Linear Models. Density Estimation. Recursive Partitioning. Scatterplot Smoothers and Additive Models. Survival Analysis. Quantile Regression. Analyzing Longitudinal Data I. Analyzing Longitudinal Data II. Simultaneous Inference and Multiple Comparisons. Missing Values. Meta-Analysis. Bayesian Inference. Principal Component Analysis. Multidimensional Scaling. Cluster Analysis. Bibliography. Index.
