1. 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

2. Outline
Differences
Similarities

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

4. 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)

5. 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)

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

7. 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

8. 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

9. QUESTIONS?