Chevron Left
Back to Causal Inference

Learner Reviews & Feedback for Causal Inference by Columbia University

3.1
stars
76 ratings

About the Course

This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. This course provides an introduction to the statistical literature on causal inference that has emerged in the last 35-40 years and that has revolutionized the way in which statisticians and applied researchers in many disciplines use data to make inferences about causal relationships. We will study methods for collecting data to estimate causal relationships. Students will learn how to distinguish between relationships that are causal and non-causal; this is not always obvious. We shall then study and evaluate the various methods students can use — such as matching, sub-classification on the propensity score, inverse probability of treatment weighting, and machine learning — to estimate a variety of effects — such as the average treatment effect and the effect of treatment on the treated. At the end, we discuss methods for evaluating some of the assumptions we have made, and we offer a look forward to the extensions we take up in the sequel to this course....
Filter by:

26 - 31 of 31 Reviews for Causal Inference

By Víthor R F

•

Jan 16, 2020

The teacher is great, but some things could be explained more clearly. Also, there are some errors in the assignments. Other from that, totally worth it!

By Weijia C

•

Jul 12, 2020

Lectures are informative, test questions practical. Whereas more delibration could be used to the writing of assessment questions and answers as there are obvious errors. Also, forum is not well-maintained leaving many questions unanswered for years.

By Matt T

•

Mar 17, 2023

This course needs updating/a rework. The topics covered are great, but the assessment problems are out of date, sometimes wrong, or do not accept the correct answer. The ideas behind the syllabus here are exactly what I want from a mid-level/graduate intro to causal inference, but this is one of the worst courses I've ever taken on Coursera.

By Alfred E

•

Feb 26, 2024

A talking lecturing on mathematics and statistics without any equations or slides. It's impossible to follow and the worst form of pedagogy. Coursera and Columbia should remove this course. It's embarassing.

By AmiReza M

•

Dec 25, 2022

Instructor does not use Notes, Whiteboard, etc. to demonstrate points. Written elaboration precedes verbal explanation in a statistics course!

By Juan J E

•

Nov 7, 2023

Really bad