R for Everyone

Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organised to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks.

Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualisation; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes

Explore R, RStudio, and R packages
Use R for math: variable types, vectors, calling functions, and more
Exploit data structures, including data.frames, matrices, and lists
Read many different types of data
Create attractive, intuitive statistical graphics
Write user-defined functions
Control program flow with if, ifelse, and complex checks
Improve program efficiency with group manipulations
Combine and reshape multiple datasets
Manipulate strings using R’s facilities and regular expressions
Create normal, binomial, and Poisson probability distributions
Build linear, generalised linear, and nonlinear models
Program basic statistics: mean, standard deviation, and t-tests
Train machine learning models
Assess the quality of models and variable selection
Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods
Analyse univariate and multivariate time series data
Group data via K-means and hierarchical clustering
Prepare reports, slideshows, and web pages with knitr
Display interactive data with RMarkdown and htmlwidgets
Implement dashboards with Shiny
Build reusable R packages with devtools and Rcpp

Author Biography

Jared P. Lander is the owner of Lander Analytics, a statistical consulting firm based in New York City, the organizer of the New York Open Statistical Programming Meetup and an adjunct professor of statistics at Columbia University. He is also a tour guide for Scott’s Pizza Tours and an advisor to Brewla Bars, a gourmet ice pop startup. With an M.A. from Columbia University in statistics and a B.A. from Muhlenberg College in mathematics, he has experience in both academic research and industry. His work for both large and small organizations spans politics, tech startups, fund raising, music, finance, healthcare, and humanitarian relief efforts. He specializes in data management, multilevel models, machine learning, generalized linear models, visualization, data management, and statistical computing.