Plus, you’ll find a host of other RStudio webinars and videos to explore via the topic menus on the left side of that page. This one-hour introduction covers how to get started quickly with the basics of research statistics in R, providing an emphasis on reading data into R, exploratory data analysis with the tidyverse, statistical testing with ANOVAs, and finally producing a publication-ready plot in ggplot2. If you are coming to R from a traditional point-and-click statistics package such as SPSS or SAS, RStudio’s Thomas Mock has created a free video webinar titled A Gentle Introduction to Tidy Statistics In R.

Spend an hour with A Gentle Introduction to Tidy Statistics In R. You may also enjoy the Basic Basics lesson unit from R-Ladies Sydney, which provides an opinionated tour of RStudio for new users and a step-by-step guide to installing and using R packages. For beginner-friendly installation instructions, we recommend the free online ModernDive chapter Getting Started with R and RStudio. These three installation steps are often confusing to first-time users. Install, RStudio, and R packages like the tidyverse. *.rdata - A file containing one or more R objects or workspaces can be created using save(), and loaded using load().No one starting point will serve all beginners, but here are 6 ways to begin learning R.*.rds - A file containing a R object can be created using saveRDS(), and loaded using readRDS().What file types are typically associated with R? Packages for literate statistical programming - weaving written reports and analysis code in one document.Rivals (and in many cases, exceeds) SAS and Stata in terms of availability of advanced statistical methods and algorithms, through availability of user-created packages.Available for Windows, Macintosh, and Linux.It also offers an Import-Wizard-like feature that allows users to import CSV, Excel, SAS (*.sas7bdat), SPSS (*.sav), and Stata (*.dta) files into R without having to write the code to do so. (You must install R before you can install RStudio.) Its interface is organized so that the user can clearly view graphs, data tables, R code, and output all at the same time. RStudio is a free, open source IDE (integrated development environment) for R. R is a free, open source software program for statistical analysis, based on the S language.