yitalu's Stars
3b1b/manim
Animation engine for explanatory math videos
kenjihiranabe/The-Art-of-Linear-Algebra
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
JWarmenhoven/ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
rmcelreath/stat_rethinking_2022
Statistical Rethinking course winter 2022
khuyentran1401/Data-science
Collection of useful data science topics along with articles, videos, and code
pymc-devs/pymc-resources
PyMC educational resources
paul-buerkner/brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
matloff/fasteR
Fast Lane to Learning R!
erikgahner/PolData
A dataset with political datasets
matloff/TidyverseSkeptic
An opinionated view of the Tidyverse "dialect" of the R language.
mca91/EconometricsWithR
📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
DataForScience/Causality
asjadnaqvi/DiD
Keeping track of what is going on with the latest DiD innovations.
compsocialscience/summer-institute
Summer Institutes in Computational Social Science
m-clark/Miscellaneous-R-Code
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
NickCH-K/EconometricsSlides
This is the repository for the slides used in the Seattle University Econometrics course
erikgahner/awesome-statistics
A curated collection of links to statistics material
amesoudi/cultural_evolution_ABM_tutorial
This tutorial shows how to create very simple simulation or agent-based models of cultural evolution in R
doehm/tidytues
Socrats/EGTTools
Toolbox for Evolutionary Game Theory.
m-clark/models-by-example
By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.
albertoacerbi/IBM-cultevo
code for the book "Individual-based models of cultural evolution. A step-by-step guide using R"
collinprather/ISLR-Python
Labs and Exercises from "An Introduction to Statistical Learning", implemented in Python.