This is a list of resources for me primarily, essentially a reminder of things to check out from time to time or links I’ve gone back to.
If you are a CSCAR client and want some resources for statistics, programming, etc., check out the CSCAR resources page.
- Use R series: for umich folks, this is electronically available
- Ropensci Packages for Open Science.
- GitHub trending
- Statsmodels Standard statistical models in Python.
- Scikit-learn Simple and efficient tools for data mining and data analysis.
- Pandas Dealing with data in an R-like way.
- Compared to R for stats
- Workshops Kerby Shedden’s workshop notes
- Workshops Marcio’s workshop notes
People, Blogs etc.
- Andrew Gelman
- Cosma Shalizi
- Chris Colah
- Christian Robert
- R Views
- Awesome List for Machine Learning
- Frank Harrell
- Elements of Statistical Learning Bible of ML by Hastie, Tibshirani, & Friedman.
- Introduction to Statistical Learning Application of the above in R.
- Advanced Data Analysis from an Elementary Point of View
- Gaussian Processes for Machine Learning Carl Rasmussen
- Discrete Choice Methods with Simulation Kenneth Train
- An introduction to psychometric theory with applications in R