Features:
- Presents concise examples and solutions to common problems in R
- Explains how to read and interpret output from statistical analyses
- Covers importing data, data handling, and creating graphics
- New edition adds chapters on R Studio and Reproducible Research
Summary:
Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis. The R Primer provides a collection of concise examples and solutions to R problems frequently encountered by new users of this statistical software. This new edition adds coverage of R Studio and reproducible research.
CONTENTS:
Preface.
Importing data.
Reading spreadsheets.
Importing data from other statistical software programs.
Exporting data. Manipulating data.
Working with data frames.
Factors.
Transforming variables.
Statistical analyses.
Descriptive statistics.
Linear models.
Generalized linear models.
Methods for analysis of repeated measurements.
Specific methods.
Model validation.
Contingency tables.
Agreement.
Multivariate methods.
Resampling statistics and bootstrapping.
Robust statistics.
Non-parametric methods.
Survival analysis.
Graphics.
High-level plots.
More advanced graphics.
Working with graphics.
Getting information.
R packages.
The R workspace.
R Studio.
Getting information.
Using R Studio for reproducible research.
Large datasets.
Bibliography.
Index.