Purpose

I recently completed a set of data science for biostatistics training exercises for graduate students. I extensively used R for Data Science and Efficient R programming to develop a set of Adventure Time R-statistics slide decks. Whilst I recognize that they are very minimal in terms of text, I hope that the general visual flow can provide a sense of the big picture philosophy that R data science and R statistics offer contemporary scientists.

Slide decks

1. WhyR? How tidy data, open science, and R align to promote open science practices.
2. Become a data wrangleR. An introduction to the philosophy, tips, and associated use of dplyr.
3. Contemporary data viz in R. Philosophy of grammar of graphics, ggplot2, and some simple rules for effective data viz.
4. Exploratory data analysis and models in R. An explanation of the difference between EDA and model fitting in R. Then, a short preview of how to highlighting modelR.
5. Efficient statistics in R. A visual summary of the ‘Efficient R Programming’ book ideas including chunk your work, efficient planning, efficient planning, and efficient coding suggestions in R.

Here is the knitted RMarkdown html notes from the course too https://cjlortie.github.io/r.stats/, and all the materials can be downloaded from the associated GitHub repo.

I hope this collection of goodies can be helpful to others.