Causal Inference with R – Experiments

Causal Inference with R – Experiments

Credential
Department

Social Science Research Institute

Intermediate

English

Free

Overview

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. Designed to teach you about concepts, methods, and how to code in R with realistic data, this course focuses on experiment design, working with data from controlled and natural experiments, and dealing with noncompliance. This course will cover:

  • Randomized experiments and statistical inference
  • Practice with published experiments
  • Common issues in experiments
  • Dealing with noncompliance in experiments
  • Long-term average treatment effects
  • Natural experiments
  • Bounds analysis
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 - Regression

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.... Learn More