The Coursera course "Exploratory Data Analysis" is primarily about exploring and analyzing data using plots. The plot tools used are packages from the programming language R.
The following lists some features of the course:
- Principles of analytic graphics. For the use of graphics in the
explorative analysis of data, some principles of analytic graphics are outlined as in the following.
- Principle 1: Show comparisons in order to compare your current hypothesis against a competing hypothesis.
- Principle 2: Show causality, mechanism and explanation giving a possible explanation for what is causing the measurements.
- Principle 3: Show multivariate data in order to get a possible hint on which variables cause data variation.
- Principle 4: Integrate multiple modes of evidence such as words, numbers, images and diagrams.
- Principle 5: Describe and document the evidence using labels, scales, sources and such.
- Principle 6: "Content is king" emphasizing relevant content of good quality.
- Exploratory graphs. For quick and dirty plots summarizing the data hence enabling exploration of basic questions and hypotheses.
- Plotting systems in R, showing how to make graph plots in R using either the base plotting system, the Lattice plotting system or the ggplot2 plotting system. The plots can be made on the screen device or on some other device such as a pdf-file.
- Clustering, for grouping data that are closest to each other according to some metric.
- Dimension reduction, for finding a set of as few variables as possible with high data variance. Fewer variables can be plotted easier and if they do good at explaining the data variance then they are preferred to higher dimensional data.
- Video lectures enabling you to stop and play parts over again if there is something you need to have repeated.
- Quizzes to check your understanding of the stuff presented in the video lectures.
- Course project to demonstrate your practical skills in working with the stuff presented in the video lectures.
- Discussion forums so you can discuss topics with possibly thousands of other course participants.
Visit the course web site here.