Latest Courses
ISTQB Artificial Intelligence Tester Sample ExamsCheck course
JAVA Programming Online Practice ExamCheck course
Programming for Kids and Beginners: Learn to Code in PythonCheck course
Practice Exams | Codeigniter 4 developer certificationCheck course
WordPress Practice Tests & Interview Questions (Basic/Adv)Check course
Git &Github Practice Tests & Interview Questions (Basic/Adv)Check course
Machine Learning and Deep Learning for Interviews & ResearchCheck course
Laravel | Build Pizza E-commerce WebsiteCheck course
101 - F5 CERTIFICATION EXAMCheck course
Master Python by Practicing 100 QuestionCheck course
ISTQB Artificial Intelligence Tester Sample ExamsCheck course
JAVA Programming Online Practice ExamCheck course
Programming for Kids and Beginners: Learn to Code in PythonCheck course
Practice Exams | Codeigniter 4 developer certificationCheck course
WordPress Practice Tests & Interview Questions (Basic/Adv)Check course
A Crash Course in Causality: Inferring Causal Effects from Observational Data

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

FREE

Add your review
Add to wishlistAdded to wishlistRemoved from wishlist 0
Add to compare
8.9/10 (Our Score)
Product is rated as #58 in category Data Science

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! The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth–oldest institution of higher education in the United States, and considers itself to …

Instructor Details

Dr. Roy is Professor and Chair of Biostatistics and Epidemiology at Rutgers University. He is Adjunct Professor at the University of Pennsylvania, and is Co-Director of the Center for Causal Inference at Penn. Dr. Roy received his PhD from the University of Michigan in 2000. Areas of Expertise: - Causal inference - Missing data - Bayesian methods - Pharmacoepidemiology Major Works: Kim C, Daniels MJ, Marcus BH, Roy JA. A framework for Bayesian nonparametric inference for causal effects of mediation. Biometrics. 2016 Aug 1. doi:10.1111/biom.12575. Roy J, Lum KJ, Daniels MJ. A Bayesian nonparametric approach to marginal structural models for point treatments and a continuous or survival outcome. Biostatistics. 2017 Jan;18(1):32-47.

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

Duration

27 hours

Year

2017

Level

Intermediate

Certificate

Yes

Quizzes

Yes

96 reviews for A Crash Course in Causality: Inferring Causal Effects from Observational Data

4.4 out of 5
58
30
6
0
2
Write a review
Show all Most Helpful Highest Rating Lowest Rating
  1. FKG

    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.

    Helpful(1) Unhelpful(0)You have already voted this
  2. Mark F

    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.

    Helpful(1) Unhelpful(0)You have already voted this
  3. Pichaya T

    Excellent courses. I gain my expectations.

    Helpful(0) Unhelpful(0)You have already voted this
  4. Vikram R

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

    Helpful(0) Unhelpful(0)You have already voted this
  5. Miguel B

    Excellent course! The lectures are very clear and easy to follow, and Professor Roy is really good at explaining the concepts in a simple way. The assignments in R are helpful for grasping the theoretical concepts. I would specially recommend this course to data scientist, who might be interested in complementing their predictive analytics skills with the the necessary ones to tackle questions about causality.

    Helpful(0) Unhelpful(0)You have already voted this
  6. Rudy M P

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

    Helpful(0) Unhelpful(0)You have already voted this
  7. Miguel B

    Excellent course! The lectures are very clear and easy to follow, and Professor Roy is really good at explaining the concepts in a simple way. The assignments in R are helpful for grasping the theoretical concepts. I would specially recommend this course to data scientist, who might be interested in complementing their predictive analytics skills with the the necessary ones to tackle questions about causality.

    Helpful(0) Unhelpful(0)You have already voted this
  8. Rudy M P

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

    Helpful(0) Unhelpful(0)You have already voted this
  9. Vlad V

    One of the best courses in Coursera, Professor with lots of experience in a backpack show how to tackle very complex problem of causal inference. This is a topic every data analyst should know doesn’t matter which industry you work or learn.

    Helpful(0) Unhelpful(0)You have already voted this
  10. Vlad V

    One of the best courses in Coursera, Professor with lots of experience in a backpack show how to tackle very complex problem of causal inference. This is a topic every data analyst should know doesn’t matter which industry you work or learn.

    Helpful(0) Unhelpful(0)You have already voted this
  11. Ignacio S R

    The course is ok, but not having access to the slides is very annoying

    Helpful(0) Unhelpful(0)You have already voted this
  12. Ignacio S R

    The course is ok, but not having access to the slides is very annoying

    Helpful(0) Unhelpful(0)You have already voted this
  13. Manuel A V S

    I have an economics background and during my undergraduate studies I took several statistics and econometric courses. The contents delivered in this course complemented my knowledge very well from another point of view. I would definitely enjoy a more advanced course dealing with other methods. The only aspect I would improve is providing the slides for further study. Other courses in Coursera do this and, honestly, I often consult the slides.

    Helpful(0) Unhelpful(0)You have already voted this
  14. Manuel A V S

    I have an economics background and during my undergraduate studies I took several statistics and econometric courses. The contents delivered in this course complemented my knowledge very well from another point of view. I would definitely enjoy a more advanced course dealing with other methods. The only aspect I would improve is providing the slides for further study. Other courses in Coursera do this and, honestly, I often consult the slides.

    Helpful(0) Unhelpful(0)You have already voted this
  15. Andrew

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

    Helpful(0) Unhelpful(0)You have already voted this
  16. Andrew

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

    Helpful(0) Unhelpful(0)You have already voted this
  17. Arka B

    gives thorough basic intro to causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  18. Arka B

    gives thorough basic intro to causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  19. Akash G

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

    Helpful(0) Unhelpful(0)You have already voted this
  20. Akash G

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

    Helpful(0) Unhelpful(0)You have already voted this
  21. Patrick W D

    Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.

    Helpful(0) Unhelpful(0)You have already voted this
  22. Patrick W D

    Excellent course. Could use a small restructuring, as I had to go through the material more than once, but otherwise, very good material and presentation.

    Helpful(0) Unhelpful(0)You have already voted this
  23. Chris C

    Could use a bit more guidance on the projects, but overall a helpful course. Gets straight to the point.

    Helpful(0) Unhelpful(0)You have already voted this
  24. clancy b

    no nonsense, in depth and practical

    Helpful(0) Unhelpful(0)You have already voted this
  25. Chris C

    Could use a bit more guidance on the projects, but overall a helpful course. Gets straight to the point.

    Helpful(0) Unhelpful(0)You have already voted this
  26. clancy b

    no nonsense, in depth and practical

    Helpful(0) Unhelpful(0)You have already voted this
  27. Bob K

    Well taught, easy to follow but potentially very important techniques

    Helpful(0) Unhelpful(0)You have already voted this
  28. Bob K

    Well taught, easy to follow but potentially very important techniques

    Helpful(0) Unhelpful(0)You have already voted this
  29. Manuel F

    Interesting introductory course about causality. Good “compilation” in just 5 weeks. Thanks!

    Helpful(0) Unhelpful(0)You have already voted this
  30. Manuel F

    Interesting introductory course about causality. Good “compilation” in just 5 weeks. Thanks!

    Helpful(0) Unhelpful(0)You have already voted this
  31. Wei F

    This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

    Helpful(1) Unhelpful(0)You have already voted this
  32. Wei F

    This course is quite useful for me to get quick understanding of the causality and causal inference in epidemiologic studies. Thanks to Prof. Roy.

    Helpful(1) Unhelpful(0)You have already voted this
  33. Mateusz K

    I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

    Helpful(2) Unhelpful(0)You have already voted this
  34. Mateusz K

    I enjoyed the course and learned basics of causal inference. What I missed was more exercises with R in order to gain more practical understanding of the material. In particular, it would be great to have exercises where you get some dataset and your task is to calculate given causal effect and you need to come up with an approach and to execute it. This would mimic more closely problems that you encounter in practice.

    Helpful(2) Unhelpful(0)You have already voted this
  35. Michael N

    Content was useful for understanding causal inference in a variety of situations. Presentation was sometimes slow even on double speed. Lectures were generally structured from abstract to concrete, which was much harder to follow than if it were presented in english first and then made abstract (Mayer, 2009).

    Helpful(0) Unhelpful(0)You have already voted this
  36. Michael N

    Content was useful for understanding causal inference in a variety of situations. Presentation was sometimes slow even on double speed. Lectures were generally structured from abstract to concrete, which was much harder to follow than if it were presented in english first and then made abstract (Mayer, 2009).

    Helpful(0) Unhelpful(0)You have already voted this
  37. Alejandro A P

    very good content. Story line is highly concise. However, Lecturer could be more stream lined the the way of explaining. He sure is a skilled guy, however.

    Helpful(0) Unhelpful(0)You have already voted this
  38. Alejandro A P

    very good content. Story line is highly concise. However, Lecturer could be more stream lined the the way of explaining. He sure is a skilled guy, however.

    Helpful(0) Unhelpful(0)You have already voted this
  39. Christopher R

    I thought this was a good overview and I’m glad I took the course, but I would have preferred more hands on programming assignments.

    Helpful(0) Unhelpful(0)You have already voted this
  40. Christopher R

    I thought this was a good overview and I’m glad I took the course, but I would have preferred more hands on programming assignments.

    Helpful(0) Unhelpful(0)You have already voted this
  41. HEF

    The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

    Helpful(0) Unhelpful(0)You have already voted this
  42. HEF

    The content is relaxing and easy to understand, yet extremely useful in real life when you are conducting experiments. The well designed quiz each week only takes a little time, but could help you to diagnose problems and remember the key points. I really love this course.

    Helpful(0) Unhelpful(0)You have already voted this
  43. Naiqiao H

    The course is very useful for beginners. The materials are clear and easy to understand.

    Helpful(0) Unhelpful(0)You have already voted this
  44. Naiqiao H

    The course is very useful for beginners. The materials are clear and easy to understand.

    Helpful(0) Unhelpful(0)You have already voted this
  45. Wayne L

    Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.

    Helpful(0) Unhelpful(0)You have already voted this
  46. Wayne L

    Very easy to follow examples and great coverage for such an important topic! The delivery sometimes get repetitive and I wish we talked more about how the uncertainties are derived.

    Helpful(0) Unhelpful(0)You have already voted this
  47. Cameron F

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

    Helpful(0) Unhelpful(0)You have already voted this
  48. Cameron F

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

    Helpful(0) Unhelpful(0)You have already voted this
  49. Xisco B

    Very interesting studies.

    Helpful(0) Unhelpful(0)You have already voted this
  50. Xisco B

    Very interesting studies.

    Helpful(0) Unhelpful(0)You have already voted this
  51. Leihua Y

    Over all, this course is extremely helpful for students who are interested in causal inference of observational data. It provides a rather comprehensive list of methods and techniques that we could use to disentangle causal effects, provided with ample supply of exercises and tests. Highly recommended! Will definitely take other courses on similar topics with the same instructor.

    Helpful(0) Unhelpful(0)You have already voted this
  52. Leihua Y

    Over all, this course is extremely helpful for students who are interested in causal inference of observational data. It provides a rather comprehensive list of methods and techniques that we could use to disentangle causal effects, provided with ample supply of exercises and tests. Highly recommended! Will definitely take other courses on similar topics with the same instructor.

    Helpful(0) Unhelpful(0)You have already voted this
  53. Vikram M

    Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

    Helpful(0) Unhelpful(0)You have already voted this
  54. Francisco P

    Hard to understand

    Helpful(0) Unhelpful(0)You have already voted this
  55. Vikram M

    Good introductory course. I wish there were more quizzes (at least another 2 more), testing our knowledge of various formulae for computing IPTW (inverse probability of treatment weights), ITT (intent to treat) and at least one more lab in R

    Helpful(0) Unhelpful(0)You have already voted this
  56. Francisco P

    Hard to understand

    Helpful(0) Unhelpful(0)You have already voted this
  57. Ruixuan Z

    Some of the materials are bit academical and away from industry, however, I found most of the materials relevant and practical.

    Helpful(0) Unhelpful(0)You have already voted this
  58. Ruixuan Z

    Some of the materials are bit academical and away from industry, however, I found most of the materials relevant and practical.

    Helpful(0) Unhelpful(0)You have already voted this
  59. Michael S

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

    Helpful(0) Unhelpful(0)You have already voted this
  60. Michael S

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

    Helpful(0) Unhelpful(0)You have already voted this
  61. olufemi B o

    The course itremendoulsy straightened my knowledge of causal evaluation

    Helpful(0) Unhelpful(0)You have already voted this
  62. olufemi B o

    The course itremendoulsy straightened my knowledge of causal evaluation

    Helpful(0) Unhelpful(0)You have already voted this
  63. Ted L

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

    Helpful(0) Unhelpful(0)You have already voted this
  64. Ted L

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

    Helpful(0) Unhelpful(0)You have already voted this
  65. Benjamin R

    I work in the field of Marketing, in a company that is actively exploring Causal Inference methods to estimate the impact of ads on the purchase behaviour. This course provided me with a solid understanding through illustrations and examples. This has changed my perception that experiments are the only answer to tease out a causal effect. Thank you Jason.

    Helpful(0) Unhelpful(0)You have already voted this
  66. Benjamin R

    I work in the field of Marketing, in a company that is actively exploring Causal Inference methods to estimate the impact of ads on the purchase behaviour. This course provided me with a solid understanding through illustrations and examples. This has changed my perception that experiments are the only answer to tease out a causal effect. Thank you Jason.

    Helpful(0) Unhelpful(0)You have already voted this
  67. Stephen M D

    After reading Pearl’s book, Causal Inference in Statistics, I found this course really put some meat on the bones, reviewing the basics and demonstrating, in a very clear and easy to understand way, how to conduct the analyses and make causal inferences. The examples in R were reasonably easy to follow and reproduce even for someone who has not used R (me).

    Helpful(0) Unhelpful(0)You have already voted this
  68. Stephen M D

    After reading Pearl’s book, Causal Inference in Statistics, I found this course really put some meat on the bones, reviewing the basics and demonstrating, in a very clear and easy to understand way, how to conduct the analyses and make causal inferences. The examples in R were reasonably easy to follow and reproduce even for someone who has not used R (me).

    Helpful(0) Unhelpful(0)You have already voted this
  69. Luca A

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

    Helpful(0) Unhelpful(0)You have already voted this
  70. Luca A

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

    Helpful(0) Unhelpful(0)You have already voted this
  71. Eva Y G

    Can not download slides which make the source material very inaccessible

    Helpful(0) Unhelpful(0)You have already voted this
  72. Eva Y G

    Can not download slides which make the source material very inaccessible

    Helpful(0) Unhelpful(0)You have already voted this
  73. Juan M C B

    Great

    Helpful(0) Unhelpful(0)You have already voted this
  74. Juan M C B

    Great

    Helpful(0) Unhelpful(0)You have already voted this
  75. Marriane M

    Very practical for beginners in causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  76. Marriane M

    Very practical for beginners in causal inference

    Helpful(0) Unhelpful(0)You have already voted this
  77. Marko B

    Clear course most of the time and a very interesting subject. The teacher covers the concepts from many angles: conceptual understanding, math, examples and R code. I like how there is little “fluff”, you learn a lot for the time given and I don’t feel any of the concepts covered are unnecessary or esoteric. The only negative is that the course could’ve benefited from more practical assignments. There are 2 R code assignments: could’ve been more. I was thinking about giving it a 5 or 4 stars and decided on 4 in case a non perfect score actually makes the instructor improve the course.

    Helpful(0) Unhelpful(0)You have already voted this
  78. Marko B

    Clear course most of the time and a very interesting subject. The teacher covers the concepts from many angles: conceptual understanding, math, examples and R code. I like how there is little “fluff”, you learn a lot for the time given and I don’t feel any of the concepts covered are unnecessary or esoteric. The only negative is that the course could’ve benefited from more practical assignments. There are 2 R code assignments: could’ve been more. I was thinking about giving it a 5 or 4 stars and decided on 4 in case a non perfect score actually makes the instructor improve the course.

    Helpful(0) Unhelpful(0)You have already voted this
  79. Alfred B

    Overall a great course. Better than other courses on causal inference on coursera. However, some of the topics (e.g. within the IPTW and IV methodologies ) were presented in a sort of general manner (intuitive). Which is obviously not a fault of the instructor and is due to the strong research nature of these topics. Personally, I can’t think of presenting, for instance, 2SLS or insights on IPTW in more detail within a crash course. Perhaps, increasing the number of weeks to 6 or 7 in order to include more detail on, e.g. 2SLS would be a good idea. What definitely helped to make up for those missed details is the practical examples parts with R. Keep up the good job!

    Helpful(0) Unhelpful(0)You have already voted this
  80. Alfred B

    Overall a great course. Better than other courses on causal inference on coursera. However, some of the topics (e.g. within the IPTW and IV methodologies ) were presented in a sort of general manner (intuitive). Which is obviously not a fault of the instructor and is due to the strong research nature of these topics. Personally, I can’t think of presenting, for instance, 2SLS or insights on IPTW in more detail within a crash course. Perhaps, increasing the number of weeks to 6 or 7 in order to include more detail on, e.g. 2SLS would be a good idea. What definitely helped to make up for those missed details is the practical examples parts with R. Keep up the good job!

    Helpful(0) Unhelpful(0)You have already voted this
  81. Jiacong L

    I learned so much from Dr. Roy by watching his great lectures. Thank you!

    Helpful(0) Unhelpful(0)You have already voted this
  82. Jiacong L

    I learned so much from Dr. Roy by watching his great lectures. Thank you!

    Helpful(0) Unhelpful(0)You have already voted this
  83. Andrew L

    Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

    Helpful(0) Unhelpful(0)You have already voted this
  84. Andrew L

    Clear deliver of engaging content. Very disappointed the course lacked an IV program or some capstone to evaluate learning. Why would you complete the course with a quiz compared to a practical assignment. I also do not understand why the slides are not available.

    Helpful(0) Unhelpful(0)You have already voted this
  85. KATONA N P

    Taking this course was a great help for me in my work. I was familiar with most of the matching methods but learning about other preprocessing methods and approaches really widened my view on how to decide what is the best way to do causal analysis on observational data. Thank you for using examples also from the field of social sciences. All in all, thank you for making this course!

    Helpful(0) Unhelpful(0)You have already voted this
  86. KATONA N P

    Taking this course was a great help for me in my work. I was familiar with most of the matching methods but learning about other preprocessing methods and approaches really widened my view on how to decide what is the best way to do causal analysis on observational data. Thank you for using examples also from the field of social sciences. All in all, thank you for making this course!

    Helpful(0) Unhelpful(0)You have already voted this
  87. Aniket G

    Superb crash course for quickly getting up to speed!

    Helpful(0) Unhelpful(0)You have already voted this
  88. Aniket G

    Superb crash course for quickly getting up to speed!

    Helpful(0) Unhelpful(0)You have already voted this
  89. Yahia E G

    Great course. I have learned a lot. I just wish to have more programming exercises to cement our knowledge.

    Helpful(0) Unhelpful(0)You have already voted this
  90. Yahia E G

    Great course. I have learned a lot. I just wish to have more programming exercises to cement our knowledge.

    Helpful(0) Unhelpful(0)You have already voted this
  91. Mario M

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

    Helpful(0) Unhelpful(0)You have already voted this
  92. Mario M

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

    Helpful(0) Unhelpful(0)You have already voted this
  93. Ayush T

    It’s really the easiest way to approach Causality someone who is not from a pure Statistics background. The approach here is different from Judea Pearl’s book and I think it’s justified because this course was not only for computer science students. This course has changed my perspective on how to work with data.

    Helpful(0) Unhelpful(0)You have already voted this
  94. Ayush T

    It’s really the easiest way to approach Causality someone who is not from a pure Statistics background. The approach here is different from Judea Pearl’s book and I think it’s justified because this course was not only for computer science students. This course has changed my perspective on how to work with data.

    Helpful(1) Unhelpful(0)You have already voted this
  95. Gautam B

    Great intro and overview of the details of Causal Inference methods

    Helpful(0) Unhelpful(0)You have already voted this
  96. Alessandro C

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

    Helpful(0) Unhelpful(0)You have already voted this

    Add a review

    Your email address will not be published. Required fields are marked *

    This site uses Akismet to reduce spam. Learn how your comment data is processed.

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

    Price tracking

    Java Code Geeks
    Logo
    Register New Account
    Reset Password
    Compare items
    • Total (0)
    Compare