This course introduces the principles of statistics, data analysis, and R programming. Using datasets from various national and international sports, you will be guided through an interactive data analysis with videos, slides, and reproducible code. There are no pre-requisites for this course, though a familiarity with other programming languages is a plus. Please contact us if there are any questions.
All datasets for this course can be found on out GitHub page.
Part 1: Basics
Section | Slides | Code | Video |
---|---|---|---|
Setup | Slides Link | Code Link | |
Motivating Example | Slides Link | Code Link | |
Reading Files | Slides Link | Code Link | |
Basics | Slides Link | Code Link | |
Data Structures | Slides Link | Code Link | |
Packages | Slides Link | Code Link | |
Probability and Statistics | Slides Link | Code Link |
Part 2: Graphics and Manipulation
Section | Slides | Code | Video |
---|---|---|---|
Look At That! | Slides Link | Code Link | |
Polishing Plots | Slides Link | Code Link | |
Layers | Slides Link | Code Link | |
Dates Times and Groups | Slides Link | Code Link | |
Plotting Map Data | Slides Link | Code Link | |
Intro to ddply | Slides Link | Code Link |
Part 3: Machine Learning and Clustering
Section | Slides | Code | Video |
---|---|---|---|
Analytics in Sports | Slides Link | Code Link | |
Machine Learning | Slides Link | Code Link | |
Regression | Slides Link | Code Link | |
Classification | Slides Link | Code Link | |
Introduction to Clustering | Slides Link | Code Link | |
Hierarchical Clustering | Slides Link | Code Link | |
Feature Selection | Slides Link | Code Link | |
Predicting the Future | Slides Link | Code Link | |
Measuring Error | Slides Link | Code Link |
Part 4: Web Scraping and Development
Section | Slides | Code | Video |
---|---|---|---|
Web Scraping | Slides Link | Code Link | |
Introduction to Shiny | Slides Link | Code Link | |
Shiny Structure | Slides Link | Code Link | |
Shiny Tools | Slides Link | Code Link |