Chevron Left
Вернуться к Причинное следствие

Отзывы учащихся о курсе Причинное следствие от партнера Колумбийский университет

3.5
звезд
Оценки: 42
Рецензии: 17

О курсе

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....
Фильтр по:

1–17 из 17 отзывов о курсе Причинное следствие

автор: Byron S

30 окт. 2018 г.

Not having access to slides and materials negates any interest in proceeding with this course.

автор: Seo-Woo C

15 мая 2019 г.

It was difficult to follow lectures without any kind of reading

автор: Max B

26 нояб. 2018 г.

Great course. Really interesting and condensed content. A perfect course for analysts and data scientists. I will be recommending this to a few of my colleagues.

For some reason there are no slides in week 1 but don't worry there are slides from week 2 onwards

автор: Yurong J

19 апр. 2020 г.

It is impossible to learn statistics without slides in the first week.

автор: John S

3 февр. 2020 г.

The first week is a throw-away, as there are no slides, just a talking head throwing notation at you. The second week at least has a blackboard, but then the assessment is broken.

автор: Agnes v B

4 авг. 2019 г.

It is a very good intro to CI with proofs and references to recent developments.

However, I have to subtract some stars because the quality in material preparation of this course is not up to usual Coursera standards: for the first week there are no slides (so it's hard to follow), and some answers in the exams are not correct. This has been pointed out on this course's discussion forums, but nobody involved in the preparation of this course replies on its discussion forums.

автор: Charles H

16 дек. 2018 г.

The selection of material is excellent and the professor covers an amazing amount of ground in a handful of lectures. Currently, however, there are many superficial problems with the course, including repeated errors in the quizzes and lectures that are confusing because the slides are missing.

автор: Lucas B

6 июня 2019 г.

A good course. Lot's of insights on Propensity Score Matching. They show good references to those willing to read some articles. Although quick classes, exercises are easy and very practical.

автор: Yanghao W

18 апр. 2020 г.

More exercises would be better!

автор: Guannan Y

25 авг. 2020 г.

I can't feel any efforts the lecturer had made to help us understand the topic.

автор: Vladislav K

12 дек. 2020 г.

Talking head is not the best way to present for presenting such subjects.

автор: Germán A

9 янв. 2021 г.

Excellent!

автор: Pablo A G V

12 июня 2020 г.

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.

автор: Víthor R F

16 янв. 2020 г.

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!

автор: Weijia C

12 июля 2020 г.

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.

автор: Raghav B

5 янв. 2021 г.

Please add slides or some teaching aids. This course is otherwise not usable

автор: Steve N

15 мая 2020 г.

I can't unsubscribe.