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Causal Inference with R - Experiments

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Descrição do Curso

Welcome to the Causal Inference with R – Experiments, the 2nd of 7 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. We’ll stay away from dense statistical math and focus instead on higher level concepts that data scientists need to always consider when examining and making inferences about experimental data. The course instructors and creators are Dr. Matt Masten (Duke University), James Speckart (Duke), Brian Aronson (Duke), Dr. Tyler Ransom (University of Oklahoma), Dr. Bentley Coffey (University of South Carolina), and Alexandra Cooper (Duke).
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  1. 1

    Introduction

    Grátis

    We introduce how experiments help us find causal connections, and take a quick look at controlled experiments.

    Reproduzir Capítulo Agora
    Course Trailer for Causal Inference with R - Experiments
    50 xp
    Introduction to Experiments
    50 xp
    Rainfall in Sonoma County and eBay sales
    50 xp
    iPhone sales and eBay sales
    50 xp
    A Quick Response
    50 xp
    Controlled Experiments
    50 xp
    Buying a New Phone: Controlled experiments
    50 xp
    Let’s Code: Comparing Ratios
    50 xp
    Buying a New Phone: Comparing Ratios
    100 xp
    Is it a Controlled Experiment?
    50 xp
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Matt Masten HeadshotMatt Masten

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