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®, …
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).
Course Info
Learning Resource Types
notes
Lecture Notes

Analyzing global data. (Figure by MIT OpenCourseWare.)