Happy Classrooms, Happy World

1. Happy Classrooms, Happy World JMP Discovery Summit Cary NC | October 25, 2018 11:00 – 11:45 am | EBC 8

2. The Challenge: Undergrad Introductory Stat Course • Authentic experience in Statistical inquiry • A comprehensive & comprehensible use case • Real data that matter • A topic that appeals and stimulates questions • Rich enough for a full course • Naturally invites multivariate thinking • Motivate further learning

3. 2016 GAISE REPORT Context: Undergraduate “Intro Stats” Course • Teach Statistical Thinking: Investigative process & Multivariate thinking • Emphasize Concepts over Computational Procedures • Variation, confounding, sampling error… • REAL DATA in context  data management, cleaning, prep • Active Learning • Technology to Explore Concepts & Analyze Data • Assessments to improve & evaluate learning

4. https://www.nytimes.com/2018/05/02/well/move/even-a-little-exercise-might-make-us-happier.htmlhttps://www.nytimes.com/2018/05/02/well/move/even-a-little-exercise-might-make-us-happier.html

5. World Happiness Report, 2018 • 156 countries ranked • Additional focus 2018: immigration • Data sources: • Gallup World Poll • World Development Indicators • WHO • Worldwide Governance Indicators http://worldhappiness.report/ed/2018/

6. What students sometimes “get” https://www.artofmanliness.com/articles/how-to-carve-turkey/ https://healthyvoyager.com/the-many-benefits-of-learning-cooking-as-a-skill/ https://www.pinterest.com/pin/13299761370887139/ https://www.thekitchn.com/cookbooks-class-164164 http://relish.com/recipes/quick-okra-saute/ https://www.cookinglight.com/cooking-101/12-cooking-skills-every-young-adult-should-learn

7. A better goal

8. Some learning objectives • recognize questions that yield to data analysis • produce & interpret graphical displays and numerical summaries • central role of variability

9. Recommended learning objectives • Use/ develop statistical models • Use/ Understanding basics inference • interpret statistical software output

10. Data Dictionary Highlights • Happiness—Cantril Life Ladder • Covariates – six possible drivers • “Dystopia”

11. Data Import • Download *.xls workbook • Excel Wizard to import

12. Data Preparation • Country names – consistency with JMP mapping • Linked columns for virtual join • Added Columns • Groups: Hi-Med-Low scoring countries • Two more groupings– OECD, UK Independent Power report • Clusters (for later) – hierarchical based on 6 other factors • “Countries of Interest” – student’s ancestral/ home countries (12) • Screen for Outliers & Missing Data (class discussion—Table 2.1)

13. Visualizing Variation: One Variable at a time • All Factors –understanding shape of a distribution (Supporting Factors) • Variation across 156 countries (Figure 2.2 WHR 2018) • Simple dot plot—Graph Builder • Histogram—binning, Normal fit • Variation across geography • World Map • What about uncertainty? • Bars—Countries of Interest with error bars

14. Exploring bivariate relationships • Variation between/ among groups • Students’ own/ancestral nations • OECD nations • The Independent’s (UK) 25 most powerful • One-Way: • Supporting Factors by Hi-Med-Low Group • Matched Pairs • Domestic vs. Foreign-Born (Figure 2.4) • Drivers: proportion explained (Fig. 2.2) • Multivariate: scatterplot matrix and correlations (Supporting factors) • Predictor screening (Fig 2.2)

15. Exploring Multivariate Relationships • Packed Bars: Top 10 in context with GDP • Extending scatterplots – Bubble plot (Table 1) • 3-D scatterplot (S.F.) • Stacked Bars: Drivers of Happiness

16. More Comparisons: Table 2.1 WHR 2018 • Are people happier since the world-wide financial crisis? • Compare Ladder scores in 2017 to 2010 • First, some data management

17. Look ahead at Model Fitting • Which factors, taken together, account best for Happiness Scores? • Are there important interaction effects? • Intuitive introduction to Model Fitting and Stepwise regression

18. Can we say the same for countries? https://www.azquotes.com/quotes/topics/unhappy-family.html

19. Contact us! rcarver@brandeis.edu Volker.Kraft@JMP.com

20. Output images

21. Outlier Screening 2015-2017

22. Missing Data

23. Thinking about SHAPE