Statistics and Visualization for Data Analysis and Inference

An abstract graphic showing a chart overlaid with a map.

Analyzing global data. (Figure by MIT OpenCourseWare.)


Cite This Resource

Resource Description

Resource Features

Course Description

A whirl-wind tour of the statistics used in behavioral science research, covering topics including: data visualization, building your own null-hypothesis distribution through permutation, useful parametric distributions, the generalized linear model, and model-based analyses more generally. Familiarity with MATLAB®, Octave, or R will be useful, prior experience with statistics will be helpful but is not essential. This course is intended to be a ground-up sketch of a coherent, alternative perspective to the "null-hypothesis significance testing" method for behavioral research (but don't worry if you don't know what this means).

Related Content

Ed Vul, and Mike Frank. RES.9-0002 Statistics and Visualization for Data Analysis and Inference. January IAP 2009. Massachusetts Institute of Technology: MIT OpenCourseWare, License: Creative Commons BY-NC-SA.

For more information about using these materials and the Creative Commons license, see our Terms of Use.