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Learner Reviews & Feedback for A Crash Course in Causality: Inferring Causal Effects from Observational Data by University of Pennsylvania

4.7
stars
568 ratings

About the Course

We have all heard the phrase “correlation does not equal causation.” What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn how causal effects are defined, what assumptions about your data and models are necessary, and how to implement and interpret some popular statistical methods. Learners will have the opportunity to apply these methods to example data in R (free statistical software environment). At the end of the course, learners should be able to: 1. Define causal effects using potential outcomes 2. Describe the difference between association and causation 3. Express assumptions with causal graphs 4. Implement several types of causal inference methods (e.g. matching, instrumental variables, inverse probability of treatment weighting) 5. Identify which causal assumptions are necessary for each type of statistical method So join us.... and discover for yourself why modern statistical methods for estimating causal effects are indispensable in so many fields of study!...

Top reviews

FF

Nov 29, 2017

The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.

AG

Feb 17, 2022

Great introduction to the field covering model synthesis of causality ideals. Glitches in assignments - make sure to check the discussion for workarounds.

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176 - 182 of 182 Reviews for A Crash Course in Causality: Inferring Causal Effects from Observational Data

By Kasra S

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Aug 14, 2021

I think there are parts in the course where further discussion is needed.

By Ignacio S R

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Apr 30, 2018

The course is ok, but not having access to the slides is very annoying

By L L

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Nov 5, 2024

good material, but lecturer is not very engaging

By Francisco P

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May 30, 2019

Hard to understand

By coursera s

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Jan 8, 2025

Insufficient replies to student questions in discussion and following code and lectures didn't provide enough information to complete the programming assignment. I ended up guessing until I got through the assignment. pointless waste of time.

By Quantum S

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Aug 31, 2025

There is an error in the assignment submission. I always get the same score 75% regardless of my answer and intentionally made everything wrong, still the same! and cannot move forward as the passing score is 80%

By Eva Y G

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Sep 28, 2019

Can not download slides which make the source material very inaccessible