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A Crash Course in Causality: Inferring Causal Effects from Observational Data に戻る

ペンシルベニア大学(University of Pennsylvania) による A Crash Course in Causality: Inferring Causal Effects from Observational Data の受講者のレビューおよびフィードバック



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!...




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.



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.


A Crash Course in Causality: Inferring Causal Effects from Observational Data: 51 - 75 / 148 レビュー

by Ted L


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

by Kin H L L


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

by Mario M


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

by JK


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

by Akorlie A N


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

by Hao L


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

by Abdulaziz T B


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

by Georges A


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

by Minha H


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

by Deleted A


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

by 朱永載


Good explanation and hands-on R practice.

Highly recommended for those working on the observational studies

by DR A N


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

by Dror G


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

by Hidemasa O


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

by Huyen N


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

by Luca A


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

by Cameron F


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

by AlexanderV


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

by Zhixin L


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

by Akash G


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

by Oleksandr P


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

by Ahinoam P


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

by Hortensia M


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

by Elizabeth


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

by Chow K M


Detailed explanations about the rationale and statistical methods to use.