How JMP is Moving the Fences in Undergraduate Higher Education

Robert H. CarverStonehill College

JMP Discovery Summit 2014

rcarver@stonehill.edu

Moving the Fences

1. Emphasize statistical literacy and develop statistical thinking

2. Use real data

3. Stress conceptual understanding, rather than mere knowledge of procedures

4. Foster active learning in the classroom

5. Use technology for developing conceptual understanding and analyzing data

6. Use assessments to improve and evaluate student learning

GAISE College Report, 2005

• Statistics in K – 12 education

• Common Core

• Abundant cheap computers

• Abundant, massive data sets in public domain

– Messy

– Incomplete

– Complex

– Complex Sampling

Environment of Higher Ed

• Which topics are no longer needed in Intro Stat?

• Which topics can move into Intro Stat?

• Which topics are too advanced for Intro Stat?

• How “real” should real data be?

• Barriers to entry and exit?

• How can we move the fences?

Where are the Fences?

The Lineup: 9 ways the JMP helps move fences

• Eye-popping, insight-building graphics

– Engaging interactive visualizations via Graph Builder, 3-D scatterplots, and Bubble plots

– Embedded and add-in simulations that illustrate important concepts

• Environment for using large, real datasets

– Creation and use of sampling weights

– Intuitive data management tools All in one package

The Lineup: 9 ways the JMP helps move fences

• Rethinking Categorization of “Advanced” Techniques

– integration of parametric & non-parametric tests

– Bootstrap Confidence Intervals

– Painless logistic regression

• “Just Like the Pros Use!”

– Outstanding support for undergraduates – menu-driven, ample documentation, help, on-screen tips…

– Removal of the DO NOT ENTER gates by eliminating or lowering barriers to entry

1. Interactive Graphics Engage & Build Understanding

2. Simulations & Animations

• Our texts imply–Data Acquisition via Complex Sampling

is “fair territory”

–Data Analysis using Stratification Weights are “foul territory” (or upper deck/ luxury boxes?)

Where are the Fences?

3. Sampling Weightsfor Newbies

3. Sampling Weightsfor Newbies

Unweighted Weighted

NHANES Data, n = 8,949

• JMP reinforces concepts of variable types/data structure

• Course project linear regression

• Multi-stage assignment, teams

• Find real data, analyze, write up conclusions

• E.g.: Do countries that spend more on health care per capita have lower fertility rates?

• Two data sources– Fertility rates – UNStats Gender data base

– Health care – World Bank WDI

4. Intuitive Data Management Tools

4. Intuitive Data Management Tools

4. Intuitive Data Management Tools

World Bank Data

4. Intuitive Data Management Tools

5. Integrating Non-Parametric Tests

6. Built-in Bootstrap

6. Built-in Bootstrap

6. Built-in Bootstrap

7. “Easy” Logistic Regression

7. “Easy” Logistic Regression

8. User Support for Learners

• Help that helps

• Tutorials

• Videos that teach

• Consistent framework

• Pictures + computation

• Linked graphs

9. The Most important Fences

Thank You

• For attending and listening

• Mia Stephens, JMP

• Students

• Organizers

• SAS Press

rcarver@stonehill.edu