Causal Inference with R – Introduction

Causal Inference with R – Introduction

Credential
Department

Social Science Research Institute

Intermediate

English

Free

Overview

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. Designed to teach you causal inference concepts, methods, and how to code in R with realistic data, this introduction focuses on how to interpret treatment effects, and how to explore and derive key summary statistics from dataframes. This course covers the following concepts:

  • Basic concepts behind causal inference
  • Introduction to treatment effects
  • Cofounders, counterfactuals, and p-hacking
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

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

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