Chevron Left
Back to A Crash Course in Causality: Inferring Causal Effects from Observational Data

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

4.7
stars
550 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

JC

Invalid date

A high quality course that delivers what it says in the title. Well-paced introduction to the potential outcomes framework, with a nice balance of theoretical and practical aspects.

PH

Invalid date

I completed all 4 available courses in causal inference on Coursera. This one has the best teaching quality. The material is very clear and self-contained!

Filter by:

101 - 125 of 175 Reviews for A Crash Course in Causality: Inferring Causal Effects from Observational Data

By Rudy M P

•

Apr 17, 2018

I learned the basics of causality inference and want even more now!

By Alessandro C

•

Mar 31, 2020

Very clear, it give good intuition also for technical points.

By keyvan r

•

Sep 1, 2020

great course and practical introduction to causal inference.

By Ziyang H

•

Jul 26, 2020

A good course with detailed explanation and data examples

By Mohammed S

•

Sep 4, 2020

Excellent course in causal effect estimation. Thanks .

By Anne G

•

Sep 18, 2022

Thank for the awesome course! Learned a great deal!

By Aniket G

•

Dec 15, 2019

Superb crash course for quickly getting up to speed!

By Zhe C

•

Apr 20, 2022

I learned a lot from this course! Highly recommend!

By Marriane M

•

Oct 8, 2019

Very practical for beginners in causal inference

By Min-hyung K

•

Jun 30, 2017

Thanks so much for providing this great lecture.

By Arka B

•

May 31, 2018

gives thorough basic intro to causal inference

By Michael S

•

Jul 7, 2019

Awesome!!! Looking forward to the next one!!!

By Tarashankar B

•

Sep 8, 2020

Detailed and excellent course on causality

By Pichaya T

•

Feb 26, 2018

Excellent courses. I gain my expectations.

By Akin A C

•

Jan 3, 2021

excellent course, very very useful!!

By Takahiro I

•

Sep 26, 2017

The best lecture series of causality

By Giuseppe D

•

Jul 20, 2024

Excellent course, very interesting!

By Clancy B

•

Aug 28, 2018

no nonsense, in depth and practical

By Carolina S

•

May 18, 2021

A very good introduction course.

By Paulo Y C

•

Aug 1, 2020

intense and well crafted course!

By William L

•

Apr 3, 2020

wonderful course, very helpful

By Bob H

•

Oct 19, 2017

Good intro of the techniques.

By Junho Y

•

Dec 21, 2020

Jason Roy! He is a monster!

By Simon J S

•

Aug 4, 2023

Great Course, Thank You!

By Xisco B T

•

May 5, 2019

Very interesting studies.