University of Pennsylvania
A Crash Course in Causality: Inferring Causal Effects from Observational Data
University of Pennsylvania

A Crash Course in Causality: Inferring Causal Effects from Observational Data

Taught in English

Some content may not be translated

40,460 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.7

(530 reviews)

Intermediate level
Some related experience required
18 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

16 quizzes

See how employees at top companies are mastering in-demand skills

Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 5 modules in this course

This module focuses on defining causal effects using potential outcomes. A key distinction is made between setting/manipulating values and conditioning on variables. Key causal identifying assumptions are also introduced.

What's included

8 videos3 quizzes

This module introduces directed acyclic graphs. By understanding various rules about these graphs, learners can identify whether a set of variables is sufficient to control for confounding.

What's included

8 videos2 quizzes

An overview of matching methods for estimating causal effects is presented, including matching directly on confounders and matching on the propensity score. The ideas are illustrated with data analysis examples in R.

What's included

12 videos5 quizzes

Inverse probability of treatment weighting, as a method to estimate causal effects, is introduced. The ideas are illustrated with an IPTW data analysis in R.

What's included

9 videos3 quizzes

This module focuses on causal effect estimation using instrumental variables in both randomized trials with non-compliance and in observational studies. The ideas are illustrated with an instrumental variables analysis in R.

What's included

9 videos3 quizzes

Instructor

Instructor ratings
4.7 (134 ratings)
Jason A. Roy, Ph.D.
University of Pennsylvania
1 Course40,460 learners

Offered by

Recommended if you're interested in Probability and Statistics

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

Showing 3 of 530

4.7

530 reviews

  • 5 stars

    77.16%

  • 4 stars

    19.24%

  • 3 stars

    1.88%

  • 2 stars

    0.75%

  • 1 star

    0.94%

WL
4

Reviewed on Mar 16, 2019

KS
5

Reviewed on Apr 4, 2021

CE
5

Reviewed on Jul 15, 2017

New to Probability and Statistics? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions