*** New and improved for Fall 2021 *** Repository for resources, codes, and data associated to an intro to MATLAB and Statistics class. This course will take you from MATDRAB to MATFAB in 8 sessions. See below for a description of each class and the content they cover.

1. Basics: environment, data types, syntax, matrix operations, strings, I/O
2. Basics: set operators, tables, cells and structs, loops, conditionals
3. Signal processing + MATLAB toolboxes (Simulating data, Hilbert transforms, filters, FFT, normalizing data, Interpolation)
4. Plotting (Tips on making stunning figures, MATLAB’s native plotting tools, Gramm) and descriptive stats
5. Statistics (correlations, t-test, permutation tests, ANOVA, SDT, AUC/ROC)
6. Data reduction and clustering (PCA, ICA, k-means)
7. Computational Models, Regressions, Model Fitting, & Model selection
8. Machine learning (Regressions cont., hierarchical models, SVM)

Each class has slides and accompanying code with examples using freely available data. Lectures will be over zoom (the link will be sent over email).

Note: RPDR data obtained from dragracer package in R

USA election data obntained from the Wikipedia

Face images obtained from: https://github.com/NVlabs/ffhq-dataset

I do not own any of the images used in this repository, they are simply used as examples