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
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 the 9 most important formulas in probability that every data scientist should understand and master to appropriately handle any project in probability| 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
This article explains in details what is the normal or Gaussian distribution, its importance in statistics and how to test if your data is normally distributed| 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 the differences between a quantitative continuous, quantitative discrete, qualitative ordinal and qualitative nominal variable via concrete examples| Stats and R