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!
Offered By
A Crash Course in Causality: Inferring Causal Effects from Observational Data
University of PennsylvaniaAbout this Course
44,682 recent views
Learner Career Outcomes
50%
started a new career after completing these courses
23%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 18 hours to complete
English
Subtitles: English
Skills you will gain
Instrumental VariablePropensity Score MatchingCausal InferenceCausality
Learner Career Outcomes
50%
started a new career after completing these courses
23%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 18 hours to complete
English
Subtitles: English
Offered by
University of Pennsylvania
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 be the first university in the United States with both undergraduate and graduate studies.
Syllabus - What you will learn from this course
4 hours to complete
Welcome and Introduction to Causal Effects
This module focuses on defining causal effects using potential outcomes. A key distinction is made between setting/manipulating values and conditioning on variables. Key causal identifying assumptions are also introduced.
4 hours to complete
8 videos (Total 128 min)
8 videos
Confusion over causality19m
Potential outcomes and counterfactuals13m
Hypothetical interventions17m
Causal effects19m
Causal assumptions18m
Stratification23m
Incident user and active comparator designs14m
3 practice exercises
Practice Quiz30m
Practice Quiz30m
Causal effects30m
2 hours to complete
Confounding and Directed Acyclic Graphs (DAGs)
This module introduces directed acyclic graphs. By understanding various rules about these graphs, learners can identify whether a set of variables is sufficient to control for confounding.
2 hours to complete
8 videos (Total 86 min)
8 videos
Causal graphs9m
Relationship between DAGs and probability distributions15m
Paths and associations7m
Conditional independence (d-separation)13m
Confounding revisited9m
Backdoor path criterion15m
Disjunctive cause criterion9m
2 practice exercises
Practice Quiz30m
Identify from DAGs sufficient sets of confounders30m
5 hours to complete
Matching and Propensity Scores
An overview of matching methods for estimating causal effects is presented, including matching directly on confounders and matching on the propensity score. The ideas are illustrated with data analysis examples in R.
5 hours to complete
12 videos (Total 171 min)
12 videos
Overview of matching12m
Matching directly on confounders13m
Greedy (nearest-neighbor) matching17m
Optimal matching10m
Assessing balance11m
Analyzing data after matching20m
Sensitivity analysis10m
Data example in R16m
Propensity scores11m
Propensity score matching14m
Propensity score matching in R15m
5 practice exercises
Practice Quiz30m
Practice Quiz30m
Matching30m
Propensity score matching30m
Data analysis project - analyze data in R using propensity score matching30m
3 hours to complete
Inverse Probability of Treatment Weighting (IPTW)
Inverse probability of treatment weighting, as a method to estimate causal effects, is introduced. The ideas are illustrated with an IPTW data analysis in R.
3 hours to complete
9 videos (Total 119 min)
9 videos
More intuition for IPTW estimation9m
Marginal structural models11m
IPTW estimation11m
Assessing balance9m
Distribution of weights9m
Remedies for large weights13m
Doubly robust estimators15m
Data example in R26m
3 practice exercises
Practice Quiz30m
IPTW30m
Data analysis project - carry out an IPTW causal analysis30m
Reviews
TOP REVIEWS FROM A CRASH COURSE IN CAUSALITY: INFERRING CAUSAL EFFECTS FROM OBSERVATIONAL DATA
by WLMar 16, 2019
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.
by MFDec 27, 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.
by FFNov 29, 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.
by OEJul 29, 2020
I enjoyed the course a lot and I think I took a lot from it as well. The quizzes and computer projects were appropriate, and the resourcees posted were very useful.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You’ll be prompted to complete an application and will be notified if you are approved. Learn more.
More questions? Visit the Learner Help Center.
