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Learner Reviews & Feedback for Causal Inference 2 by Columbia University
11 ratings
About the Course
This course offers a rigorous mathematical survey of advanced topics in 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 advanced topics in causal inference, including mediation, principal stratification, longitudinal causal inference, regression discontinuity, interference, and fixed effects models.
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1 - 5 of 5 Reviews for Causal Inference 2
By Ang K J
•Aug 24, 2020
Reading off the slides, no real explanation of concepts or notes provided.
By Samuel D
•Apr 05, 2020
No engaging. Unable to complete the tasks
By Huyen
•May 02, 2020
This course is painful. Lots of dry maths with no relatable examples. Difficult to follow.
By Weijia C
•Aug 16, 2020
Too few and easy assessment questions that does not help understand the course much
By Vikram M
•Oct 21, 2019
Terrible
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