Global Certificate in Causal Interactions
-- ViewingNowThe Global Certificate in Causal Interactions is a comprehensive course designed to equip learners with essential skills in causal inference, a highly sought-after skill in today's data-driven world. This course is critical for professionals who want to gain a deeper understanding of the cause-and-effect relationships in data and make informed decisions based on data insights.
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โข Causal Inference: Introduction to causal interactions, understanding the concept of causality, and differentiating it from correlation. โข Study Designs: Experimental and observational study designs, potential outcomes framework, and randomization. โข Propensity Score Matching: Concept and application of propensity score methods in causal inference. โข Regression Analysis: Linear and logistic regression models, their assumptions, and application in causal inference. โข Difference-in-Differences: Concept, identification assumptions, and estimation methods for difference-in-differences designs. โข Instrumental Variables: Understanding instrumental variables, their assumptions, and estimation methods. โข Panel Data Analysis: Fixed effects and random effects models, and their application in causal inference. โข Sensitivity Analysis: Quantitative and qualitative sensitivity analysis methods in causal inference. โข Causal Graphical Models: Directed acyclic graphs (DAGs), d-separation, and adjustment criteria for back-door paths.
Note: This list of units is not exhaustive and serves as a general guideline for creating a Global Certificate in Causal Interactions. Additional units or topics may be added or removed based on the specific needs and goals of the course.
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