NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 2 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Jennifer Hill; George Perrett; Stacey A. Hancock; Le Win; Yoav Bergner – Statistics Education Research Journal, 2024
Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…
Descriptors: Statistics Education, Causal Models, Statistical Inference, College Students
Jennifer Hill; George Perrett; Vincent Dorie – Grantee Submission, 2023
Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…
Descriptors: Causal Models, Statistical Inference, Artificial Intelligence, Data Analysis