What Is Programming? And How To Get Started
January 28, 2025
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(98 reviews)
(98 reviews)
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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.
4 videos2 readings
3 videos1 reading1 assignment
3 videos1 reading1 assignment
3 videos1 reading1 assignment
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3 videos2 readings1 assignment
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.
Fundação Instituto de Administração
Course
Johns Hopkins University
Course
American Psychological Association
Specialization
University of Michigan
Specialization
98 reviews
34.69%
22.44%
14.28%
6.12%
22.44%
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Reviewed on Jun 11, 2020
Great course. Really interesting and condensed content. However, It was difficult to follow lectures without any kind of reading and there wasn't any support on the discussion forums.
Reviewed on Jan 15, 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!
Reviewed on Apr 7, 2022
Assignments are a mess, and apparently haven't been fixed for years after multiple complaints. Otherwise a good course, although not better than the one from U of PA, which was more accessible IMO.
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