This course is designed for those who are new to the study of probability, or those who are seeking an approachable review of core concepts prior to enrolling in a college-level statistics course.
There are two parts of this course. The first part comprises five lessons that introduce the theory of causal diagrams and describe its applications to causal inference. The second part presents a series of case studies that highlight the practical applications of causal diagrams to real-world questions from the health and social sciences.
Causal Diagrams: Draw Your Assumptions Before Your Conclusions
In this course, learners will be working with practitioners in social, life, and physical sciences to understand how calculus and mathematical models play a role in their work.