Learn how to use simulations and for loops in R to answer a probability question such as What is the probability that two persons have the same initials?| Stats and R
Learn to use the dplyr R package which helps you to solve the most common data manipulation challenges such as filtering, summarizing or sorting observations| Stats and R
In this post, I highlight the 10 most common errors in R and how to fix them. I also mention a couple of warnings (which are different than errors).| Stats and R
Learn when and how to do a one-sample Wilcoxon test in R. See also how to visualize and interpret the results with a concrete example.| Stats and R
Learn how to run multiple and simple linear regression in R, how to interpret the results and how to verify the conditions of application| Stats and R
Learn how to do the Wilcoxon test (non-parametric version of the Student's t-test) in R, used to compare 2 groups when the normality assumption is violated| Stats and R
Learn how to compare groups for multiple variables at once in R thanks to a Student t-test or ANOVA and communicate the results in a better way| Stats and R
Discover the best RStudio addins, how to use them in practice and how they can help you when writing code in R or R Markdown| Stats and R
Learn how to perform a descriptive analysis of your data in R, from simple descriptive statistics to more advanced graphics used to describe your data at hand| Stats and R
This article illustrates the main tips, tricks and shortcuts you can use in RStudio and R Markdown to write code more quickly and more efficiently| Stats and R