Matlab is a statistical analysis package and scripting language widely in the engineering and social sciences to design and conduct studies, collect behavioral data, run standard and non-standard statistical analyses, and visualize multivariate data. It is an intuitive yet powerful language that can facilitate many aspects of the research process. This CSASS Short Course is intended to provide you with the basic tools to use Matlab effectively in your research. Some amount of practice is required to become comfortable with Matlab, but the effort is greatly rewarded.
You can find information about obtaining student and academic copies of Matlab at www.mathworks.com/products/matlab/
2018-2019 workshops:
Introduction to Matlab for the social sciences (Oct 19, 2018)
This workshop introduced students and faculty to MATLAB, a statistical analysis package and scripting language that allows users a wide range of tools to conduct standard and nonstandard statistical analyses and visualize multivariate data. I showed a variety of examples of data analyses from different social science disciplines. No previous experience necessary.
Matlab tools for collecting and analyzing behavioral data (Nov 2, 2018)
This workshop introduced behavioral research tools, including how to design a basic behavioral study, how to collect responses (such as button presses and mouse clicks) and reaction times from participants, and how to save and load individual and group data.
Previous workshops:
Workshop 1: Introduction to Matlab
(presented 10/25/2013, 12/8/2014, 11/15/2015, 11/28/2016, 10/20/2017)
The first workshop covers the basics of Matlab: setting up and starting Matlab, using the Command and Editor windows, defining variables, entering data, conducting standard statistical analyses, and basic plotting.
Workshop 2: Research Tools
(presented 11/1/2013, 12/10/2014, 4/21/2016)
The second workshop covers a variety of research tools in Matlab, including how to design a basic behavioral study, how to collect responses and reaction times from participants, and how to save and load data.
Workshop 3: Data Analysis and Plotting
(presented 11/8/2013, 12/12/2014, 1/24/2017)
The third workshop gets into more detail on data analysis and plotting using tools from Matlab’s statistics toolbox. Analyses covered include t-tests, ANOVA, correlation, and multiple regression. Plotting functions include scatter and line plots, bar graphs, and histograms.
Workshop 4: Visualizing Multivariate Data
(presented 6/10/2014, 6/5/2015)
As social scientists, we often encounter highly complex, multivariate data that is hard to characterize in standard 2D plots. This workshop covers techniques that help visualize multivariate, include 3D plots, surface plots, and dynamic displays. There is also a short introduction to PCA (principal components analysis).
Workshop 5: The Bootstrap Method
(presented 2/28/2017, 5/11/2018 )
In this workshop I introduce the Bootstrap Method which involves random resampling with replacement and produces estimates of standard errors and confidence intervals for different statistical measures, with minimal assumptions about the underlying distributions. I also cover rank statistics and other nonparametric and simulation methods.