Introduction to Statistical Thinking and Data Anal (PUBH97052)

Most of the R code I used during the module Introduction to Statistical Thinking and Data Analysis, offered to master students in Epidemiology, Public Health, etc. I aim to explain all assumptions and how to prove/test them in R, create regression models, see the correlation, apply statistical tests like c-statists and t-test and much more (see the document keywords to see the content).

A complete explanation of the "Introduction to Statistical Thinking and Data Analysis" given to students enrolled in MSc in Public Health, Epidemiology etc. Here you will find a straightforward explanation of many statistical tools, from hypothesis testing, t-test, missing data and sample size to P-values, distributions (binomial, Poisson, etc.), correlation (e.g. Pearson's and Spearman), and assess key features of datasets and several regression assumptions. Most chapters have real...