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Comentários e feedback de alunos de A Crash Course in Causality: Inferring Causal Effects from Observational Data da instituição Universidade da Pensilvânia

230 classificações
77 avaliações

Sobre o curso

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!...

Melhores avaliações


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.


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.

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26 — 50 de {totalReviews} Avaliações para o A Crash Course in Causality: Inferring Causal Effects from Observational Data

por Ted L

Aug 24, 2019

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

por Mario M

Jan 12, 2020

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

por Joon-Ku I

Oct 24, 2017

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

por 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.

por 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.

por Michael L

Nov 26, 2017

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

por DR A N

Aug 22, 2017

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

por Huyen

May 02, 2020

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

por Luca A

Sep 24, 2019

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

por Cameron F

Apr 05, 2019

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

por Akash G

Jun 17, 2018

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

por 张采蔚

Aug 04, 2019

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

por Vikram R

Mar 14, 2018

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

por olufemi B o

Aug 23, 2019

The course itremendoulsy straightened my knowledge of causal evaluation

por Bob K

Oct 16, 2018

Well taught, easy to follow but potentially very important techniques

por Gautam B

Feb 18, 2020

Great intro and overview of the details of Causal Inference methods

por Rudy M P

Apr 17, 2018

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

por Alessandro C

Mar 31, 2020

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

por Aniket G

Dec 16, 2019

Superb crash course for quickly getting up to speed!

por Marriane M

Oct 08, 2019

Very practical for beginners in causal inference

por Min-hyung K

Jul 01, 2017

Thanks so much for providing this great lecture.

por Arka B

May 31, 2018

gives thorough basic intro to causal inference

por Michael S

Jul 08, 2019

Awesome!!! Looking forward to the next one!!!

por Pichaya T

Feb 26, 2018

Excellent courses. I gain my expectations.

por Takahiro I

Sep 26, 2017

The best lecture series of causality