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Causal Inference with R - Regression

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Course Description

Welcome to the 3rd course in our 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 course focuses on how to use regression to find causal effects, why they can be controversial, and what they look like in practice. 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 data. The course instructors and creators are Dr. Matt Masten (Duke University), James Speckart (Duke), Brian Aronson (Duke), Dr. Tyler Ransom (University of Oklahoma), and Alexandra Cooper (Duke).
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  1. 1

    Regressions 1: Introduction to Regression As Causality

    Free

    This chapter will introduce you to using regression analysis to find causal effects

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    Course Trailer for Causal Inference with R - Regression
    50 xp
    Introduction to Regression Analysis
    50 xp
    Interpreting Regressions
    50 xp
    Reversing Causal Direction
    50 xp
    Let’s Code: Comparing Hospital Quality to Mortality Rates
    50 xp
    Comparing Hospital Quality to Mortality Rates
    100 xp
    Regression Models and Policy Implementation
    50 xp
    Basic Elements of a Regression Table
    50 xp
    Reading a Bivariate Regression Table
    50 xp
    Reading a Multivariate (Multiple) Regression Table
    50 xp
    The Relationship between Economic Development and Property Rights
    50 xp
    Regressions with small coefficients and small confidence intervals
    50 xp
    Recalling terminology
    50 xp
    Multiple Regression Models
    50 xp
    Let’s Code: Running a Regression Model
    50 xp
    Running a Regression Model: A Simple Beginning
    100 xp
    Running a Regression Model: Improving Our Model
    100 xp
    Steps Prior to Analysis with Regression Models
    50 xp
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Matt Masten HeadshotMatt Masten

I'm an econometrician working on identification and causal inference.
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SSRI @ Duke University HeadshotSSRI @ Duke University

We create modular online educational content for Duke University's Social Science Research Institute to share with students and professionals around the world. If you have any feedback for us about any part of this course, please let us know!
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Alexandra Cooper HeadshotAlexandra Cooper

Alexandra Cooper earned a Ph.D. in political science from the University of North Carolina at Chapel Hill and has taught at Duke, UNC, UNC-Charlotte, and most recently, at Lafayette College, before joining Duke University to plan and develop the Social Science Research Institute (SSRI). Initially responsible for SSRI's day-to-day programming and operations, as the institute has grown and added staff, she has had the opportunity to focus on coordinating educational programming. Her key responsibilities include organizing workshops and events, and supporting programming focused on improving knowledge and applications of the tools and methods of the social and behavioral sciences.
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Bentley Coffey HeadshotBentley Coffey

I have an unquenchable curiosity and a passion for policy, with an emphasis on the environment. I have studied an unusually broad array of subjects, with a tendency for my analysis to go deep into rigorous modeling and statistics. Yet, my style is casual and flexible...
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