John Hopkins University - Exploratory Data Analysis 

Introduction

Installing R on Windows (3.2.1)

Installing R on a Mac (3.2.1)

Installing R Studio (Mac)

Setting Your Working Directory (Windows)

Setting Your Working Directory (Mac)

Principles of Analytic Graphics

Exploratory Graphs (part 1)

Exploratory Graphs (part 2)

Plotting Systems in R

Base Plotting System (part 1)

Base Plotting System (part 2)

Base Plotting Demonstration

Graphics Devices in R (part 1)

Graphics Devices in R (part 2)

1 practice exercise

Week 2 - Welcome to Week 2 of Exploratory Data Analysis. This week covers some of the more advanced graphing systems available in R: the Lattice system and the ggplot2 system. While the base graphics system provides many important tools for visualizing data, it was part of the original R system and lacks many features that may be desirable in a plotting system, particularly when visualizing high dimensional data. The Lattice and ggplot2 systems also simplify the laying out of plots making it a much less tedious process.

Lattice Plotting System (part 1)

Lattice Plotting System (part 2)

ggplot2 (part 1)

ggplot2 (part 2)

ggplot2 (part 3)

ggplot2 (part 4)

ggplot2 (part 5)

1 practice exercise

Week 3 - Welcome to Week 3 of Exploratory Data Analysis. This week covers some of the workhorse statistical methods for exploratory analysis. These methods include clustering and dimension reduction techniques that allow you to make graphical displays of very high dimensional data (many many variables). We also cover novel ways to specify colors in R so that you can use color as an important and useful dimension when making data graphics. All of this material is covered in chapters 9-12 of my book Exploratory Data Analysis with R.

Hierarchical Clustering (part 1)

Hierarchical Clustering (part 2)

Hierarchical Clustering (part 3)

K-Means Clustering (part 1)

K-Means Clustering (part 2)

Dimension Reduction (part 1)

Dimension Reduction (part 2)

Dimension Reduction (part 3)

Working with Color in R Plots (part 1)

Working with Color in R Plots (part 2)

Working with Color in R Plots (part 3)

Working with Color in R Plots (part 4)

Week 4 - This week, we'll look at two case studies in exploratory data analysis. The first involves the use of cluster analysis techniques, and the second is a more involved analysis of some air pollution data. How one goes about doing EDA is often personal, but I'm providing these videos to give you a sense of how you might proceed with a specific type of dataset.

Clustering Case Study

Air Pollution Case Study

Practical R Exercises in swirl Part 4

Post-Course Survey