I have made a number of tutorials on a variety of R- and statistics-related topics. The list below shows descriptions of and links to these tutorials. Keep an eye on this page – I’m always adding more!

## R packages

across: a summary of the

`across()`

function which replaces the select helper functions such as`select_if()`

and`mutate_at()`

in dplyr 1.0.0tidymodels: an introduction to the tidymodels package for conducting Machine Learning in a tidy way

purrr: an introduction to the purrr R package for iteration

The tidyverse: a two part summary of the tidyverse, aimed at helping practitioners transition from base R to the tidyverse. Part 1 focuses on tidy thinking, piping, dplyr and ggplot2, and Part 2 focuses on tidyr, purrr, readr, tibbles as well as lubridate, forcats and stringr

recipes: an introduction to using the recipes R package for pre-processing data prior to machine learning

scoped verbs: a summary of the usage of dplyr scoped verbs such as

`mutate_if()`

,`summarise_all()`

,`rename_at()`

caret: an introduction to caret prepared for STAT215A. (Jupyter notebook)

ggplot2: ggplot2 basics prepared for a workshop at Joint Genome Institute. (Jupyter notebook)

interactive visualization: a tutorial on interactive viz prepared for the SGSA student seminar series

superheat I made a super cool R package (blog post, github, vignette, paper, video) for creating customizable, extendable, and beautiful heatmaps

## Statistics

- ANOVA: an intuitive explanation of ANOVA prepared for the Practical Statistics group.

## Causal Inference

## Data Science

A consistent and reproducibile workflow: a github repository that contains a guide for a consistent and reproducible data science project workflow.

A detailed data science workflowexample: a detailed description of my data science project workflow.