Learn how to analyze and visualize Universal Analytics (UA) and Google Analytics 4 (GA4) data for your blog or website via the googleAnalyticsR package in R| 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 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 about the 7 seven main benefits and reasons of having a data science blog and sharing your code, expertise and knowledge through your blog| Stats and R
Learn how to compute a correlation coefficient (Pearson and Spearman) and perform a correlation test in R| 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
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