Revolutionizing Introductory Statistics Education

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Explore the challenges faced in teaching introductory statistics, the need for a holistic approach focusing on modern data and problem-solving, and strategies to engage students effectively. Embrace a shift towards relevant, practical, and engaging statistical education for the 21st century.

  • Statistics Education
  • Data Science
  • Modern Approach
  • Problem-Solving
  • Introductory Stats

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  1. Intro Stats in the 21 Intro Stats in the 21st stCentury Century Dick De Veaux Williams College JSM -- Seattle Aug 9, 2015

  2. WHAT KEEPS ME UP AT NIGHT WHAT KEEPS ME UP AT NIGHT Data Scientists teaching our course Students think that Statistics is irrelevant for their lives and work Students think that Statistics is essentially univariate We continue to change the course around the edges - With Resampling the exception 8/9/15 JSM Seattle

  3. THE PROBLEM THE PROBLEM We teach the wrong stuff We teach it the wrong way We teach it in the wrong order Other than that, we re doing really well 8/9/15 JSM Seattle

  4. WHATS WRONG? WHAT S WRONG? The course has passed its best by date - Small data sets - Mathematical - Students still produce the results - Inference with unrealistic assumptions 8/9/15 JSM Seattle

  5. A HOLISTIC APPROACH A HOLISTIC APPROACH Instead - Modern data (Rob Gould) - Models - Problem solving Why not preach what we practice? A Holistic approach to Intro Stats This approach requires Judgment, brains and Maturity Harold Hill

  6. HOW TO GET TO THE COOL STUFF? HOW TO GET TO THE COOL STUFF? Start with it we need to speed up! Chris Wild Introduce models early - Motivate univariate questions from more complex models - Socratic method What to leave out - Mathematics of Sampling distributions We just need the concept Is resampling the answer ? Yes . And no. - Getting under the hood with methods 8/9/15 JSM Seattle

  7. DIAMONDS DIAMONDS Four C s: - Carat, Color, Cut, Clarity 8/9/15 JSM Seattle

  8. COLOR COLOR 8/9/15 JSM Seattle

  9. PRICE BY COLOR PRICE BY COLOR

  10. HERES WHY HERE S WHY 8/9/15 JSM Seattle

  11. HOW MUCH IS A FIREPLACE WORTH? HOW MUCH IS A FIREPLACE WORTH? The Data - 1729 randomly selected homes from the county records of Saratoga New York about 2005. - Conclusions are only about the Northeast 8/9/15 JSM Seattle

  12. Starting Starting Univariate Univariate 8/9/15 JSM Seattle

  13. PRICE BY FIREPLACE? PRICE BY FIREPLACE? No 740 $174,653 Yes 988 $239,914 Difference $65,620 8/9/15 JSM Seattle

  14. WAIT A MINUTE WAIT A MINUTE

  15. Relationship with size Relationship with size

  16. WHAT IF WE FIT TWO LINES? WHAT IF WE FIT TWO LINES? Difference now is $5567

  17. WHAT IF WE LET THEM GO? WHAT IF WE LET THEM GO?

  18. THE ANSWER IS. THE ANSWER IS . It depends !

  19. THE TITANIC THE TITANIC Ticket Class Crew First Second Third 118 167 285 Total 212 673 885 202 123 325 178 528 706 710 1491 2201 Lived Died Total Survival Survivors Non-Survivors Class Crew First Second Third

  20. WHY NOT? WHY NOT? F M | Adult 3 1,2,C Child 2 or 3 1 or Crew 3 1 or 2 46% 93% Crew 1st 14% 27% 100% 23% 33% You ve cracked the resampling egg, why not enjoy the omelette?

  21. WHERE ARE WE? WHERE ARE WE? Introduce models early - Motivate univariate questions from more complex models - Not the other way around! Use complex questions and models to drive topics Statistics is more than a collection of tools - Which ones are really important? How much should we ask them to produce ? 8/9/15 JSM Seattle

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