Kari Lock Morgan Department of Statistics Penn State University

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Presentation transcript:

Kari Lock Morgan Department of Statistics Penn State University Teaching Introductory Statistics Using Simulation-Based Inference Methods Kari Lock Morgan Department of Statistics Penn State University JSM 2017 Baltimore, MD August 3rd, 2017

Outline Differences Similarities

Course format & delivery Face-to-face (Paul, Laura, Matt) Large enrollment (Laura, Matt) Online (Whitney) Blended (Casey)

Students First stat course Second course Private elite university (All but Casey) Second course (Casey) Private elite university (Paul) General undergraduates (Paul, Casey, Laura) Small elite liberal arts college (Casey) Biology/health undergraduates (Matt) Large public university (Whitney, Laura, Matt) Adult learners (Whitney)

Instructors Professor with full control (Paul, Casey, Matt) Instructor with little/no control (Whitney, Laura) Knowledge of simulation (Paul, Casey, Matt) New to simulation (Whitney, Laura) Not new to teaching (All but Laura) New to teaching (Laura)

Minitab Express & StatKey Technology DataDesk (Paul) Minitab Express & StatKey (Whitney, Matt) R (Casey) JMP & StatKey (Laura)

Order Descriptive statistics & Simulation inference By parameter or method? Paul: Descriptive statistics & Simulation inference Traditional inference Whitney: Descriptive statistics Simulation & Traditional inference Casey: Descriptive statistics Traditional inference Simulation Laura, Matt: Descriptive statistics Simulation inference Traditional inference

Similarities Simulation for conceptual understanding Simulation AND traditional inference Not a complete redesign! Spreads out “impossible” concepts / natural scaffolding of concepts Less reliance on abstract theoretical math Students perform as well or better non-SBI Instructor preference for SBI

QUESTIONS?