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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

449 classificações
146 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


11 de set de 2021

Great introduction on the causal analysis.The instructor did a great job on explaining the topic in a logical and rigorous way. R codes are very relevant and helpful to digest the material as well.


27 de dez de 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.

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51 — 75 de 148 Avaliações para o A Crash Course in Causality: Inferring Causal Effects from Observational Data

por Ted L

24 de ago de 2019

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

por Kin H L L

11 de mar de 2022

Covered from mathematical concepts to practical statistical analysis with R. A perfect course for newcomers on causal inference.

por Mario M

12 de jan de 2020

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

por JK

24 de out de 2017

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

por Akorlie A N

28 de dez de 2020

Excellent course. This course helped me to develop my intuition on some of the more abstract concepts in causality.

por Hao L

31 de ago de 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

11 de ago de 2017

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

por Georges A

20 de dez de 2020

Excellent course, extremely well presented that helps clarify a lot of statistical concepts in an intuitive way.

por Minha H

3 de jul de 2021

Good course to review key techniques in causal inference. Would be nice to have more in-depth course in sequel.

por Deleted A

26 de nov de 2017

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

por 朱永載

25 de jul de 2022

Good explanation and hands-on R practice.

Highly recommended for those working on the observational studies

por DR A N

22 de ago de 2017

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

por Dror G

18 de jan de 2021

Very enlightening. Well explained, and strikes a great balance between theory & practical aspects.

por Hidemasa O

28 de dez de 2020

This course is actually great. It is a basic course but it does not mean it is for an amateur.

por Huyen N

1 de mai de 2020

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

por Luca A

24 de set de 2019

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

por Cameron F

5 de abr de 2019

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

por AlexanderV

10 de out de 2021

Great course, nice balance between statistical theory and practical application using R

por Zhixin L

25 de jan de 2021

Extremely helpful for people who just started to do research on observational studies!

por Akash G

17 de jun de 2018

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

por Oleksandr P

28 de dez de 2020

Great course. It is good for broad set of people with different level of math skill.

por Ahinoam P

27 de dez de 2020

Great course for getting good intuitions on central concepts in causal inference

por Hortensia M

9 de abr de 2021

excelent!!!, this is a great course. The teacher is really good explaining.

por Elizabeth

8 de abr de 2021

Great intro to causality with great examples and sample R code. Thank you!

por Chow K M

6 de abr de 2021

Detailed explanations about the rationale and statistical methods to use.