Data Analysis with R, Second Edition: A comprehensive guide to manipulating, analyzing, and visualizing data in R, Edition 2
About this ebook
- *]Analyze your data using R – the most powerful statistical programming language
- [*]Learn how to implement applied statistics using practical use-cases
- [*]Use popular R packages to work with unstructured and structured data
- Gain a thorough understanding of statistical reasoning and sampling theory
- Employ hypothesis testing to draw inferences from your data
- Learn Bayesian methods for estimating parameters
- Train regression, classification, and time series models
- Handle missing data gracefully using multiple imputation
- Identify and manage problematic data points
- Learn how to scale your analyses to larger data with Rcpp, data.table, dplyr, and parallelization
- Put best practices into effect to make your job easier and facilitate reproducibility
Budding data scientists and data analysts who are new to the concept of data analysis, or who want to build efficient analytical models in R will find this book to be useful. No prior exposure to data analysis is needed, although a fundamental understanding of the R programming language is required to get the best out of this book.
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About the author
Tony Fischetti is a data scientist at College Factual, where he gets to use R everyday to build personalized rankings and recommender systems. He graduated in cognitive science from Rensselaer Polytechnic Institute, and his thesis was strongly focused on using statistics to study visual short-term memory. Tony enjoys writing and contributing to open source software, blogging at onthelambda, writing about himself in third person, and sharing his knowledge using simple, approachable language and engaging examples. The more traditionally exciting of his daily activities include listening to records, playing the guitar and bass (poorly), weight training, and helping others.
