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.)


Dr. Ed Vul

Dr. Mike Frank

Resource Features

Resource 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 MATLABĀ®, 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).