Slides

If the slides here aren’t updated or you are just interested in what the rmarkdown files look like, you can find the source files in the courses/stat486/slides/ folder in the github repository for my website.

Review

• Probability - R Code
• Statistics - R Code
• Regression - R Code

Data Wrangling in R

• Introduction to R - R Code
• Data Visualization - R Code
• Data Transformation - R Code
• Data Wrangling - R Code

Programming in R

• R Objects - R Code
• Logical Operations - R Code
• Control Flow - R Code
• Functions - R Code

Monte Carlo Methods

• Distributions - R Code
• Monte Carlo Methods - R Code
• Estimator evaluation - R Code
• Interval coverage - R Code
• Continuous time Markov process - R Code

Modeling

• Binomial analyses - R Code
• Normal analyses - R Code
• Linear regression - R Code
• Logistic regression - R Code
• Poisson regression - R Code

Reproducibility

• Data Science
• Rscripts - R Code
• Rmarkdown
• Interactivity - Rmd
• Shiny - R Code

Machine learning

• Introduction to ML - R Code
• Penalized regression - R Code
• Random forests - R Code
• Prediction - R Code