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 perform the Kruskal-Wallis test in R (the nonparametric version of the ANOVA) to compare 3 groups or more under the non-normality assumption| Stats and R
Select the most appropriate statistical (hypothesis) test based on the number of variables and their types with the help of a flowchart| Stats and R
Learn how to track the performance of your blog or website in R by analyzing page views, sessions, users and engagement with the {googleAnayticsR} package| Stats and R
Learn how to perform an Analysis Of VAriance (ANOVA) in R to compare 3 groups or more. See also how to interpret the results and perform post-hoc tests| Stats and R
Learn how to create professional graphics and plots in R (histogram, barplot, boxplot, scatter plot, line plot, density plot, etc.) with the ggplot2 package| 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
Learn how to apply the Student's t-test by hand and in R in order to compare two independent or paired samples with known or unknown variances| Stats and R
Make the the most correlated variables stand out via a correlogram. See also how to enhance a correlation plot to show significant correlations among variables| 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
Learn how to perform a descriptive analysis of your data by hand. You will learn how to compute both location and dispersion measures to describe your data| Stats and R
Learn about the five most common data types in R, numeric, integer, character, factor and logical. See also how to recognize the different data types in R| Stats and R