Causal Inference with R – Regression

Causal Inference with R – Regression

Credential
Department

Social Science Research Institute

Intermediate

English

Free

Overview

Causal Inference with R – Regression is the third of seven courses on causal inference concepts and methods created by Duke University with support from eBay, Inc. Designed to teach you causal inference concepts, methods, and how to code in R with realistic data, this course focuses on how to use regression to find causal effects, why they can be controversial, and what they look like in practice. This course will cover:

  • Introduction to regression as causality
  • Using regression to estimate causal effects
  • Introduction to matching methods
Statistics & Data Analysis / Open online course

Causal Inference with R - Introduction

Causal Inference with R is the first course in a seven-part series on causal inference concepts and methods created by Duke University with support from eBay, Inc.... Learn More

Statistics & Data Analysis / Open online course

Causal Inference with R - Experiments

Causal Inference with R – Experiments is the second of seven courses on causal inference concepts and methods created by Duke University with support from eBay, Inc.... Learn More