1. ISCAT Faculty Development Workshop Allan Rossman and Beth Chance Cal Poly – San Luis Obispo June 21-25, 2004

2. ISCAT workshop 2 Overview - Outline Workshop goals, format, binder The problem  Motivation/audience  Principles  Course materials Content, Structure, Status

3. June 21-25, 2004 ISCAT workshop 3 Workshop Goals - Primary To help prepare you to  Present a course that provides a more balanced introduction to statistics for mathematically inclined students  Infuse a post-calculus introductory statistics course with activities and data  Model recommended pedagogy and content for future teachers of statistics

4. June 21-25, 2004 ISCAT workshop 4 Workshop Goals - Secondary To generate productive thought and discussion about appropriate  Goals  Content  Pedagogy of an introductory statistics course for mathematically inclined students

5. June 21-25, 2004 ISCAT workshop 5 Workshop Goals - Secondary (cont.) Offer helpful guidance for  Implementing activities and data  Assessing student learning  Using technology effectively in such a course Provide an enjoyable, collegial experience

6. June 21-25, 2004 ISCAT workshop 6 Workshop Format Most sessions will consist of working through activities/investigations  Please be willing to play the role of student  Investigations chosen from throughout course to illustrate guiding principles  We’ll “lecture” more than with our students  We’ll offer implementation suggestions along the way

7. June 21-25, 2004 ISCAT workshop 7 Workshop Format (cont.) Some discussion sessions focused on particular issues  Goals/content  Implementation/assessment  We’d love to hear feedback from you at any point during and after this workshop Also corner us during breaks, meals, beginning and end of day Email discussion list

8. June 21-25, 2004 ISCAT workshop 8 Workshop Binder Logistical information  Campus map, workshop schedule  Biographical sketches Course materials  We’ll work through a small subset this week  May want to record your work on tablet paper Additional activities, materials  Articles  Sample syllabi, exams, homework, review  More to come

9. June 21-25, 2004 ISCAT workshop 9 Features of Statistics Education Reform Active Learning Conceptual Understanding Genuine Data Use of Technology Communication Skills Interpretation in Context Authentic Assessment

10. June 21-25, 2004 ISCAT workshop 10 Products of Statistics Education Reform Textbooks Activity Books Lab Manuals Books of Data Sources Books of Case Studies On-line Books Journals Dynamic Software Java Applets Web Sites Project Templates Assessment Instruments Workshops

11. June 21-25, 2004 ISCAT workshop 11 What’s the Problem? Vast majority of reform efforts have been directed at the “Stat 101” service course Rarely reaches Mathematics or Statistics majors  Option A: Take Stat 101  Option B: Standard Prob and Math/Stat sequence

12. June 21-25, 2004 ISCAT workshop 12 What’s the Problem? Option A  Does not challenge students mathematically  Rarely counts toward major Option B  Does not give balanced view of discipline  Fails to recruit all who might be interested  Leaves prospective K-12 teachers ill-prepared to teach statistics, implement reform methods  Does not even prepare assistants for Stat 101!

13. June 21-25, 2004 ISCAT workshop 13 Is This Problem Important? “The question of what to do about the standard two-course upperclass sequence in probability and statistics for mathematics majors is the most important unresolved issue in undergraduate statistics education.” - David Moore

14. June 21-25, 2004 ISCAT workshop 14 Is This Problem Important? “The standard curriculum for mathematics majors allows little time for statistics until, at best, an upper division elective. At that point, students often find themselves thrust into a calculus-based mathematical statistics course, and they miss many basic statistical ideas and techniques that are at the heart of high school statistics courses.” - CBMS MET report (ch. 5)

15. June 21-25, 2004 ISCAT workshop 15 Is This Problem Important? “In most teacher preparation programs appropriate background in statistics and probability will not be provided by simply requiring a standard probability- statistics course for mathematics majors. It is essential to carefully consider the important goals of statistical education in designing courses that reflect new conceptions of the subject.” - CBMS MET report (ch. 5)

16. June 21-25, 2004 ISCAT workshop 16 Our Project To develop and provide a: Data-Oriented, Active Learning, Post-Calculus Introduction to Statistical Concepts, Applications, Theory Supported by the NSF DUE/CCLI #9950476, 0321973

17. June 21-25, 2004 ISCAT workshop 17 Principle 1 Motivate with real studies, genuine data  Statistics as a science  Wide variety of contexts  Some data collected on students themselves

18. June 21-25, 2004 ISCAT workshop 18 Principle 2 Emphasize connections among study design, inference technique, scope of conclusions  Issues arise in chapter 1, recur often  Observational study vs. controlled experiment  Randomization of subjects vs. random sampling  Inference technique follows from randomization in data collection process

19. June 21-25, 2004 ISCAT workshop 19 Principle 3 Conduct simulations often  Problem-solving tool and pedagogical device  Address fundamental question: “How often would this happen in the long run?”  Hands-on simulations usually precede technological simulations  Java applets  Small-scale Minitab programming (macros)

20. June 21-25, 2004 ISCAT workshop 20 Principle 4 Use variety of computational tools  For analyzing data, exploring statistical concepts  Assume that students have frequent access to computing Not necessarily every class meeting in computer lab  Choose right tool for task at hand Analyzing data: statistics package (e.g., Minitab) Exploring concepts: Java applets (interactivity, visualization) Immediate feedback from calculations: spreadsheet (Excel)

21. June 21-25, 2004 ISCAT workshop 21 Principle 5 Investigate mathematical underpinnings  Primary distinction from “Stat 101” course  Some use of calculus but not much  Will assume familiarity with mathematical ideas such as function  Example: study principle of least squares in univariate and bivariate settings  Often occurs as follow-up homework exercises

22. June 21-25, 2004 ISCAT workshop 22 Principle 6 Introduce probability “just in time”  Not the goal  Studied as needed to address statistical issues  Often introduced through simulation  Examples Hypergeometric distribution: Fisher’s exact test for 2x2 table Binomial distribution: Sampling from random process Continuous probability models as approximations

23. June 21-25, 2004 ISCAT workshop 23 Principle 7 Foster active explorations  Students learn through constructing own knowledge, developing own understanding  Need direction, guidance to do that

24. June 21-25, 2004 ISCAT workshop 24 Principle 8 Experience entire statistical process over and over  Data collection  Graphical and numerical displays  Consider inference procedure  Apply inference procedure  Communicate findings in context  Repeat in new setting Repeat in new setting  Repeat in new setting…

25. June 21-25, 2004 ISCAT workshop 25 Content- Chapter 1 Comparisons and conclusions  Categorical variables  Two-way tables  Relative risk, odds ratio  Variability, confounding, experimental design, randomization, probability, significance  Fisher’s exact test

26. June 21-25, 2004 ISCAT workshop 26 Content- Chapter 2 Comparisons with quantitative variables  Visual displays  Numerical summaries  Randomization distribution Significance, p-value, …

27. June 21-25, 2004 ISCAT workshop 27 Content- Chapter 3 Sampling from populations and processes  Bias, precision  Random sampling  Sampling variability, distributions  Bernoulli process and binomial model Binomial approximation to hypergeometric  Significance, confidence, types of errors

28. June 21-25, 2004 ISCAT workshop 28 Content- Chapter 4 Models and sampling distributions  Probability models, including normal  Approximate sampling distribution for sample proportion Normal approximation to binomial  Sampling distribution of sample mean t-procedures  Bootstrapping

29. June 21-25, 2004 ISCAT workshop 29 Content- Chapter 5 Comparing two populations  Categorical variables Two-sample z-test Approximation to randomization distribution Odds ratio  Quantitative variables Two-sample t-test Approximation to randomization distribution

30. June 21-25, 2004 ISCAT workshop 30 Content- Chapter 6 Association and relationships  Chi-square tests  Analysis of variance  Simple linear regression

31. June 21-25, 2004 ISCAT workshop 31 Course Materials- Structure Investigations  Can be adapted for variety of teaching styles Exposition  Study conclusions, discussion, summaries Technology explorations Detours for terminology, probability Practice problems  Help students to assess their understanding  Expand their knowledge

32. June 21-25, 2004 ISCAT workshop 32 Course Materials- Status Preliminary version to be published by Duxbury in August  Hot-off-the-press version in your binders  Companion website: www.rossmanchance.com/iscam/ Next year: polishing, refining, developing resource materials  Homework problems/solutions, teachers’ guide, powerpoint, practice problem solutions to appear on web  Include more worked out examples Please share your suggestions with us

33. June 21-25, 2004 ISCAT workshop 33 Questions? On the workshop? On the course materials? Ready to play the role of (good) student now?