A Crash Course in Causality: Inferring Causal Effects from Observational Data(으)로 돌아가기

# 펜실베이니아 대학교의 A Crash Course in Causality: Inferring Causal Effects from Observational Data 학습자 리뷰 및 피드백

4.7
별점
280개의 평가
92개의 리뷰

## 강좌 소개

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!...

## 최상위 리뷰

MF

Dec 28, 2017

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

Nov 30, 2017

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.

필터링 기준:

## A Crash Course in Causality: Inferring Causal Effects from Observational Data의 92개 리뷰 중 26~50

교육 기관: Arnab S

Nov 24, 2017

I was a novice in causal analysis. But I needed some education in counterfactual estimation. This course provided me with the necessary knowledge and tools. I especially enjoyed the matching, IPTW and IV chapters. Thank you!

교육 기관: Pak S H

Sep 07, 2020

I completed all 4 available courses in causal inference on Coursera. This one has the best teaching quality. The material is very clear and self-contained!

교육 기관: Andrew

May 16, 2018

This course is really fantastic for all levels. Very thorough explanations and helpful illustrations. Many thanks for putting this together!

교육 기관: Ted L

Aug 24, 2019

Well structured to provide solid understanding of fundamentals, good intuition, and a basic view of applying the covered material.

교육 기관: Mario M

Jan 12, 2020

Great introduction. Immediately used new knowledge in current job (marketing data scientist). Recommended course to co-workers.

교육 기관: Joon-Ku I

Oct 24, 2017

To those with some advanced statistics background, this would truly be helpful to catch up econometric thought processes.

교육 기관: Hao L

Aug 31, 2017

Not only good for bio stats, it has also profound impact to my understanding of a/b testing in the internet world.

교육 기관: Abdulaziz T B

Aug 12, 2017

This is an excellent course taught by a very competent professor in a very simple to understand and intuitive way.

교육 기관: Michael L

Nov 26, 2017

Excellent overview on causality inference and handling confounders combined with practical examples and R code.

교육 기관: DR A N

Aug 22, 2017

Excellent course! Can make it longer though and cover more details and latest advances and issues :-)

교육 기관: Huyen

May 02, 2020

The best course on causal inference on Coursera. Lots of examples, easy to follow materials.

교육 기관: Luca A

Sep 24, 2019

A clear and straight-to-the-point introduction to causality. I'm really enjoying the course!

교육 기관: Cameron F

Apr 05, 2019

Good course on the over view of Causality. Not too technical, but not too light and fluffy.

교육 기관: Akash G

Jun 17, 2018

Amazing Course! Really Helpful. I would love to have a similar full-duration course :D

교육 기관: CAIWEI Z

Aug 04, 2019

This course is very suitable for beginners, clear and easy to understand.

교육 기관: Vikram R

Mar 14, 2018

Great course for getting your hands dirty with some real causal methods.

교육 기관: olufemi B o

Aug 23, 2019

The course itremendoulsy straightened my knowledge of causal evaluation

교육 기관: Bob K

Oct 16, 2018

Well taught, easy to follow but potentially very important techniques

교육 기관: Gautam B

Feb 18, 2020

Great intro and overview of the details of Causal Inference methods

교육 기관: Rudy M P

Apr 17, 2018

I learned the basics of causality inference and want even more now!

교육 기관: Alessandro C

Mar 31, 2020

Very clear, it give good intuition also for technical points.

교육 기관: keyvan R

Sep 01, 2020

great course and practical introduction to causal inference.

교육 기관: Ziyang H

Jul 27, 2020

A good course with detailed explanation and data examples

교육 기관: Mohammed S U

Sep 04, 2020

Excellent course in causal effect estimation. Thanks .

교육 기관: Aniket G

Dec 16, 2019

Superb crash course for quickly getting up to speed!