STAT 186 - Introduction to Causal Inference Learning Course

[STAT 186 - Introduction to Causal Inference Learning Course] STAT 186 - Introduction to Causal Inference STAT 186 introduces students to causal inference methods used to identify and estimate causal effects in observational and experimental studies. The course covers topics such as potential outcomes framework, randomized experiments, propensity score matching, and causal graphs (Bayesian networks, DAGs). Students learn how to design studies that allow for causal inference, apply statistical techniques to control for confounding variables, and interpret causal relationships from data. Through theoretical foundations and practical examples, students gain skills in assessing causality, addressing biases in observational studies, and making causal claims based on statistical evidence. STAT 186 prepares students for advanced coursework in epidemiology, public policy evaluation, social sciences, and research involving causal inference methodologies.This Learning Course is a platform that helps students to study and learn. The platform provides all the required material for the students to study. The material includes Study guide, Exam Questions & Answers, Study Notes and other resources that are useful for the students. It also gives information about the upcoming exams so that students can prepare themselves accordingly.