This workshop offers a crash course on graphics and regression models in R. Topics covered include multiple regression, model comparison, mixed-effects models, and the construction of graphical displays using the ggplot2 package. This is an intermediate workshop appropriate for those already familiar with R.
This accelerated introduction will help you quickly get up to speed with the R statistical computing language. We will introduce the basics of the R language syntax, data import and management, package installation, and basic programming concepts including functions, classes and methods, iteration, and debugging. No prior R knowledge is required, but previous experience statistical or technical computing (e.g., Matlab, SAS, Stata, Python, and of course R) will be helpful.
This introduction to the popular ggplot2 R graphics package will show you how to create a wide variety of graphical displays in R. Topics covered included aesthetic mapping and scales, faceting, and themes. This is an intermediate level workshop appropriate for those already familiar with R. Participants should be familiar with importing and saving data, data types (e.g., numeric, factor, character), and manipulating data.frames in R.
This hands-on, intermediate R course will guide users through a variety of programming functions in the open-source statistical software program, R. This workshop is free for Harvard and MIT affiliates. Click here to sign up!
This hands-on, intermediate R course will demonstrate a variety of statistical procedures using the open-source statistical software program, R. Topics covered include multiple regression, multilevel models, and multiple imputation. We expect that users enrolled in this course are already familiar with the statistical processes that we cover and are interested in learning how to run these procedures in R. Prerequisite: Basic familiarity with R, such acquired through an introductory R workshop.
Get an introduction to R, the open-source system for statistical computation and graphics. With hands-on exercises, learn how to import and manage datasets, create R objects, install and load R packages, conduct basic statistical analyses, and create common graphical displays. This workshop is appropriate for those with little or no prior experience with R.