Introduction to Statistics and R
As part of a tutorial for the Institute of Coding at the University of Sunderland the following lectures cover an introduction to statistics for programmers, and an introduction to R, building on the topics learned in the first lecture. These lectures are freely available as slides (linked and embedded below).
Video screencasts of these lectures are hosted on YoutTube as a playlist, with the first 3 videos going through the Introduction to Statistics portion and the last 3 videos going through the Introduction to R portion.
Introduction to Statistics
This lecture covers the basics of statistics, including descriptive and inferential statistics, the frequentist approach to probability and inference, distributions, the basics of the general linear model, extending the general linear model to categorical and multifactorial data, and checking assumptions of the general linear model.
The slides for this lecture can be found here and embedded below:
Introduction to R
This lecture is a quick introduction to R. It focuses on some basics of installing R and RStudio locally or working online via RStudio Cloud. This session is designed as a code-along activity covering reading in data, cleaning and summarising it with tables and plots, and modelling the data. This is not meant as an introduction to the R syntax, but is more a taster of how quickly you can do complex analyses using the tidyverse family of functions.
The lecture can be found here and embedded below: