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byui_m221_book_r

Introductory Statistics in R

causal_inference_tutorial

Exploring how probability theory can be modified to handle causal relationships directly through the do-calculus and structured causal models.

causal_ml_econ

cl-demo

Command line demonstration

cmf-macro

Macroeconomic course for CMF

columbia-ma-math-camp-2020

Hosts material for Columbia MA Math Camp 2020

complete-python-3-bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

computing-bootcamp-2019

Duke University :: Department of Statistical Science Computing Bootcamp 2019

course-intro-econometrics

course-intro-macroeconomics

course-intro-microeconomics

course-program-evaluation

course-public-utility-economics

Syllabus for a course at Portland State University covering both energy, water, transportation and telecomunications.

course_econ202

ECON202: Intermediate Macroeconomics

coursera-machine-learning-andrewng-python

This contains notes and exercises made in Python I made a long time ago from the Andrew Ng course in Coursera.

coursera-ml

Exercises from Andrew Ng's Machine Learning on Coursera in Matlab/Octave, R and Python

coursera-ml-r

I'm working through Andrew Ng's popular machine learning course in R

covid19-stata-tutorials

Files used in the online articles

crimebythenumbers

This book introduces the programming language R and is meant for undergrads or graduate students studying criminology. R is a programming language that is well-suited to the type of work frequently done in criminology - taking messy data and turning it into useful information. While R is a useful tool for many fields of study, this book focuses on the skills criminologists should know and uses crime data for the example data sets.Notes for using R in criminology research

csss564-labs-2019

Lab materials for CSSS 564: Bayesian Statistics for the Social Sciences. Spring 2019 at the University of Washington

data-viz-workshops

data-wrangling-econ-book

dataviz_2022gserm

Visualizing and Communicating Data with R

depocenbootcamp

materials for self learning

designscistud

Sample course materials that can be used with Design and Analysis of Experiments and Observational Studies using R

discrete-choice-models

My practices on Kenneth Train's Exercises in R.

distillblog

distill blog

dive-into-machine-learning

Dive into Machine Learning with Python Jupyter notebook and scikit-learn!

dlaicourse

Notebooks for learning deep learning

doingmathwithpython.github.io

Website for "Doing Math With Python"