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返回到 A Crash Course in Causality: Inferring Causal Effects from Observational Data

學生對 宾夕法尼亚大学 提供的 A Crash Course in Causality: Inferring Causal Effects from Observational Data 的評價和反饋

4.7
324 個評分
111 條評論

課程概述

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!...

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MF
2017年12月27日

I really enjoyed this course, the pace could be more even in parts. Sometimes the pace could be more even and some more books/reference material for further study would be nice.

FF
2017年11月29日

The material is great. Just wished the professor was more active in the discussion forum. Have not showed up in the forum for weeks. At least there should be a TA or something.

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101 - A Crash Course in Causality: Inferring Causal Effects from Observational Data 的 111 個評論(共 111 個)

創建者 Naiqiao H

2019年2月27日

The course is very useful for beginners. The materials are clear and easy to understand.

創建者 Fernando C

2017年11月24日

They could offer more applied exercises in R. But, it was also great.

創建者 Lyons B

2020年9月20日

The lectures are good, and they might consider covering more topics.

創建者 Gavin M

2020年12月4日

It was well laid out, and overall helpful.

創建者 Javed A

2020年11月27日

A good course. Bit difficult for novices.

創建者 Juan C

2019年10月7日

Great

創建者 Andrew L

2019年11月28日

Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

創建者 Ignacio S R

2018年4月30日

The course is ok, but not having access to the slides is very annoying

創建者 Francisco P

2019年5月30日

Hard to understand

創建者 Siyu H

2021年2月14日

This is a very theoretical course with much math formula and less well-explained practical examples to better illustrate those formula. I came to this course hoping to learn about new ideas and techniques of experiment design for causal effect when randomized experiments are not possible. Unfortunately I did not achieve this goal. This is just my personal view. If you come with a different purpose, you might find this course more useful than I did.

創建者 Eva Y G

2019年9月28日

Can not download slides which make the source material very inaccessible