Data Analysis with R: Click here to enter text.

• [*]Load, manipulate and analyze data from different sources
• [*]Gain a deeper understanding of fundamentals of applied statistics
• [*]A practical guide to performing data analysis in practice

• [*]Navigate the R environment
• [*]Describe and visualize the behavior of data and relationships between data
• [*]Gain a thorough understanding of statistical reasoning and sampling
• [*]Employ hypothesis tests to draw inferences from your data
• [*]Learn Bayesian methods for estimating parameters
• [*]Perform regression to predict continuous variables
• [*]Apply powerful classification methods to predict categorical data
• [*]Handle missing data gracefully using multiple imputation
• [*]Identify and manage problematic data points
• [*]Employ parallelization and Rcpp to scale your analyses to larger data
• [*]Put best practices into effect to make your job easier and facilitate reproducibility

Whether you are learning data analysis for the first time, or you want to deepen the understanding you already have, this book will prove to an invaluable resource. If you are looking for a book to bring you all the way through the fundamentals to the application of advanced and effective analytics methodologies, and have some prior programming experience and a mathematical background, then this is for you.