This example-based general introduction to the statistical computing environment does not assume any previous familiarity with R or other software packages. R functions are compellingly presented in the context of interesting applications with real data.

R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.

The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.

Illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics Provide a general introduction to the R system and provides an overview of the capabilities of R to perform basic numerical and graphical summaries of data R functions are presented in the context of interesting applications with real data

Autorentext

Maria Rizzo is Associate Professor in the Department of Mathematics and Statistics at Bowling Green State University.

Jim Albert is Professor of Mathematics and Statistics at Bowling Green State University.

Inhalt
Introduction.- Quantitative Data.- Categorical Data.- Presentation Graphics.- Exploratotry Data Analysis.- Basic Inference Models.- Regression.- Analysis of Variance I.- Analysis of Variance II.- Randomiczation tests.- Simulation Experiments.- Bayesian Modeling.- Monte Carlo Methods.