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Bewertung und Feedback des Lernenden für A Crash Course in Causality: Inferring Causal Effects from Observational Data von University of Pennsylvania

449 Bewertungen

Über den Kurs

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!...



11. Sep. 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. Dez. 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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76 - 100 von 148 Bewertungen für A Crash Course in Causality: Inferring Causal Effects from Observational Data


4. Aug. 2019

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

von Vikram R

14. März 2018

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

von olufemi B o

22. Aug. 2019

The course itremendoulsy straightened my knowledge of causal evaluation

von Bob K

16. Okt. 2018

Well taught, easy to follow but potentially very important techniques

von Gautam B

17. Feb. 2020

Great intro and overview of the details of Causal Inference methods

von Rudy M P

17. Apr. 2018

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

von Alessandro C

31. März 2020

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

von keyvan R

1. Sep. 2020

great course and practical introduction to causal inference.

von Ziyang H

27. Juli 2020

A good course with detailed explanation and data examples

von Mohammed S

4. Sep. 2020

Excellent course in causal effect estimation. Thanks .

von Aniket G

15. Dez. 2019

Superb crash course for quickly getting up to speed!

von Zhe C

21. Apr. 2022

I learned a lot from this course! Highly recommend!

von Marriane M

8. Okt. 2019

Very practical for beginners in causal inference

von Min-hyung K

1. Juli 2017

Thanks so much for providing this great lecture.

von Arka B

31. Mai 2018

gives thorough basic intro to causal inference

von Michael S

7. Juli 2019

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

von Tarashankar B

8. Sep. 2020

Detailed and excellent course on causality

von Pichaya T

26. Feb. 2018

Excellent courses. I gain my expectations.

von Akin A C

3. Jan. 2021

excellent course, very very useful!!

von Takahiro I

26. Sep. 2017

The best lecture series of causality

von Clancy B

28. Aug. 2018

no nonsense, in depth and practical

von Carolina S

18. Mai 2021

A very good introduction course.

von Paulo Y C

2. Aug. 2020

intense and well crafted course!

von William L

3. Apr. 2020

wonderful course, very helpful

von Bob H

19. Okt. 2017

Good intro of the techniques.