Tutorial: Graphical Exploratory Data Analysis

Antony Unwin, Ausbourg University, 86135 Augburg, Germany


Professor Antony Unwin
Dept of Computer-Oriented Statistics and Data Analysis
University of Augsburg
86135 Augsburg


Graphical data analysis means using graphics to discover and present information in datasets. This course discusses the role graphics play in analysis and how they can complement and support statistical modelling.

Graphical data analysis is useful for data cleaning, exploring data, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. It is essential for exploratory data analysis and data mining. R’s flexibility and its range of visualization tools make it an excellent software for graphical analysis.

Participants should have a knowledge of standard statistical graphics and experience of carrying out data analysis. Participants are welcome to bring their own laptops and datasets to explore graphical analyses for themselves, especially in the discussion sessions.


The course has three sections and two dataset discussion sessions in groups.

1) Introduction
     Goals, Definitions
     Data Cleaning

2) Exploratory Data Analysis
      Interactive methods
      Conditioning, subsetting, selection sequences
      EDA in practice (hands-on software session)

(coffee break)

3) Visualising multivariate data
      Introduction to Mosaic plots and variations
      Review of Parallel coordinate plots

4) Dataset discussion session in groups with laptops.