CS 1173 Computation for Scientists and Engineers
Data Analysis and Visualization Using MATLAB
Summary page

This course is being developed by Kay Robbins in the Department of Computer Science at the University of Texas at San Antonio with support from the National Science Foundation under DUE 0837248: Teaching computing to biologists through data visualization. CS 1173 was offered for the first time in the fall semester of 2008. The course is organized into lessons, laboratories, projects, and quizzes:

If you would like additional information or are interested in implementing a similar course at your institution, please contact her by email at krobbins@cs.utsa.edu.

Lessons

Lesson Topic Lesson linkScript link Lesson linkQuestions link
1 Editing plots Lesson 1   Lesson 1 Questions
2 Working with line graphs Lesson 2 Lesson 2 Script Lesson 2 Questions
3 Bar charts and pies Lesson 3 Lesson 3 Script Lesson 3 Questions
4 Subplots, multiple axes, and insets Lesson 4 Lesson 4 Script Lesson 4 Questions
5 Basic statistical indicators Lesson 5 Lesson 5 Script Lesson 5 Questions
6 Scatter plots, curve fitting and correlation Lesson 6 Lesson 6 Script Lesson 6 Questions
7 Rates of change Lesson 7 Lesson 7 Script Lesson 7 Questions
8 Vector logic for specializing plots Lesson 8 Lesson 8 Script Lesson 8 Questions
9 Program control Lesson 9 Lesson 9 Script Lesson 9 Questions
10 Histograms Lesson 10 Lesson 10 Script Lesson 10 Questions
11 Box plots Lesson 11 Lesson 11 Script Lesson 11 Questions
12 Error bars Lesson 12 Lesson 12 Script Lesson 12 Questions
13 Depicting confidence and significance Lesson 13 Lesson 13 Script Lesson 13 Questions
14 Tests for normality and other distributions Lesson 14 Lesson 14 Script Lesson 14 Questions
15 Hypothesis testing Lesson 15 Lesson 15 Script Lesson 15 Questions
16 Logarithmic scales and growth rate Lesson 16 Lesson 16 Script Lesson 16 Questions
17 Modeling the heart Lesson 17 Lesson 17 Script Lesson 17 Questions
18 Working with dates Lesson 18 Lesson 18 Script Lesson 18 Questions
19 Input and output Lesson 19 Lesson 19 Script Lesson 19 Questions

Laboratories

Lab Title Lab link
1 Diabetes in the US Laboratory 1
2 Daily core temperature variations in horse and shrew Laboratory 2
3 Can chirp rate predict temperature? Laboratory 3

Exams

Exams Covers

Projects

Project link Topic

Reviews and explanations

Link Topic
Hand calculation worksheet (HW2) Practice with manipulating arrays
Review of percentages Reviews of different types of percentage problems and shows how these ideas can be extended to MATLAB programs.
Statistical indicators Discusses statistical indicators such as mean, median and standard deviation and how to compute them in MATLAB
Hand calculation worksheet (HW3) Pies, bars and more practice with arrays
Interpretation of box plots explains the various facets of the box plot visualization
Populations and samples Explains how characteristics of a population can be estimated from samples
Dimensional analysis Shows how to derive conversion formulas by making sure that the units are correct
Hand calculations of statistical indicators Introduces statistical indicators such as mean, median, standard deviation, percentiles, and inter-quartile range and shows how to compute these quantities by hand
Hand calculation worksheet (HW5) Practice with pencil and paper graphing and calculation of basic indicators
Statistical indicators Discusses statistical indicators such as mean, median and standard deviation and how to compute them in MATLAB
Statistical indicator worksheet (HW7) Practice with computing basic statistical indicators
Compound interest and mortgage payments Introduces discrete-time dynamical systems using compound interest and mortgage payments as an illustration
Vector indexing worksheet Provides practice with vector indexing in a practical setting

MATLAB syntax

Link Topic
MATLAB array basics Reviews different ways to reshape and assemble arrays in MATLAB
The diff function explains how the diff function works
The max function explains how the max function works
The mean function explains how the mean function works
The median function explains how the median function works
The min function explains how the min function works
The repmat function explains how the repmat function works
The reshape function explains how the reshape function works
The std function explains how the std function works.
Subplot arrangement explains how the arguments of the subplot function control the tiling of axes
Sum function Explains how the arguments of the sum function work

Writing resources

Link Topic

Movies

Link Topic
Movie preview Introduction to Lesson 2
Narrated slides or or Slides only The Five W's of data reporting

Other handouts

Link Topic

Other links of interest

This course summary was written by Kay A. Robbins of the University of Texas at San Antonio and last modified on 21-Feb-2012. Please contact krobbins@cs.utsa.edu with comments or suggestions.