This series of workshops is designed to teach students how to conduct reproducible statistical analyses in R. The course is appropriate for students with some basic knowledge of statistics and little or no experience working in R. [The first workshop covers the basics of R][1]: you’ll learn what R is, how it compares to other statistical software, and the very basics, like how to write and save scripts in R Studio, how to create new variables, and how to import and ‘clean’ data. You’ll also learn how to effectively google for help in R. [The second workshop covers data summary and visualization][2]: how to make plots and summary tables that can help you detect errors, understand your variables, and characterize their relationships to one another. [The third workshop covers simulations and statistical tests][3]: how to evaluate whether the patterns you observe might appear even if there was no ‘true’ population effect. You’ll learn how to do this whether you are interested in comparing groups (t-tests, anovas) or examining covariance (correlations, regressions) in both R and Jamovi. [The final workshop covers reporting results][4]: using R Markdown to present results in ways that make errors unlikely and using statcheck to detect errors. [1]: https://osf.io/y63nz/ [2]: https://osf.io/r98vw/ [3]: https://osf.io/ugjzw/ [4]: https://osf.io/sh3te/