Summary and Schedule

The best way to learn how to program is to do something useful, so this introduction to MATLAB is built around a common scientific task: data analysis. Our real goal isn’t to teach you MATLAB, but to teach you the basic concepts that all programming depends on. We use MATLAB in our lessons because:

  1. we have to use something for examples;
  2. it’s well-documented;
  3. it has a large (and growing) user base among scientists in academia and industry; and
  4. it has a large library of packages available for performing diverse tasks.

But the two most important things are to use whatever language your colleagues are using, so that you can share your work with them easily, and to use that language well.

GNU Octave

GNU Octave is a free and open-source alternative to MATLAB which shares its syntax (see more about compatibility). Thus, if you don’t have access to MATLAB, you can easily set up Octave on your computer and still work through the lesson.


To begin tackling this lesson, you will need to:

  • Understand the concepts of files and directories, and the concept of a “working directory”.
  • Know how to start up MATLAB, and access the command window (which generally has a >> prompt).
  • Know how to create, edit and save text files.

Overview of the data

We are studying inflammation in patients who have been given a new treatment for arthritis, and need to analyze the first dozen data sets. The data sets are stored in Comma Separated Values (CSV) format: each row holds information for a single patient, and the columns represent successive days. The first few rows of our first file, inflammation-01.csv, look like this:


We want to:

  • load that data into memory,
  • calculate the average inflammation per day across all patients, and
  • plot the result.

To do all that, we’ll have to learn a little bit about programming.

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

You will need to install MATLAB or GNU Octave to do this lesson.

You will also need to download some data, which we will analyze using MATLAB:

  1. Download and move the file to your Desktop.

  2. Extract the zip archive. This will create a matlab-novice-inflammation directory containing the data files used in the lesson. Note that on Windows, double-clicking on the zip file simply previews the contents: to extract, right-click and select Extract All

  3. You can access this folder from the Unix shell with:


cd Desktop/matlab-novice-inflammation/