1. How Math Can Help You Choose the Right College Dr. Geoff Turner

2. What Today’s Talk WON’T Do Sadly, I can’t tell you what your ideal college is. Nor can I provide an algorithm for finding your ideal college. (But then again, no one can.) Not how psychologists typically use math.

3. What Today’s Talk Will (Hopefully) Do Let you know how psychologists make decisions and think about how people make decisions (using math) Suggest ideas to help you in your search for a college Available on the web –web.simmons.edu/~turnerg/choice/choice.ppt

4. Math in Psychology Statistical significance: A difference is not always a difference!

5. Math in Psychology Statistical significance: A difference is not always a difference!

6. Significant Differences

8. Detecting Deception Do “lie detectors” really work?

9. Polygraph Test It works!

10. Polygraph Test Oops!

11. How Psychologists Judge Differences

12. The Mathematical Models

13. Choices, Choices 1.People don’t like choosing (deciding) 2.People have surprisingly little insight into their own thought processes. 3.People’s choices are remarkably inconsistent over time, even under apparently identical conditions. 4.Frequently, our choices are not optimal. They’re irrational.

14. What’s for dinner? If offered the choice between beef and chicken, you might choose beef. Beef ≻ Chicken

15. What’s for dinner? If offered the choice between chicken and fish, you might choose chicken. Chicken ≻ Fish

16. What’s for dinner? If offered the choice between fish and beef, then, of course you would choose … Fish ≻ Beef ? Beef ≻ Fish ?

17. How is this possible? Beef ≻ Chicken Chicken ≻ Fish Fish ≻ Beef What’s for dinner?

18. Problem with Decision Models Intransitivity (the paper, rock, scissors problem) The transitive property If a > b, and b > c, then a > c but…

19. Back to Dinner Beef ≻ Chicken (Taste) Chicken ≻ Fish(Taste) Fish ≻ Beef (Health) 1 decision, but 2 dimensions

20. Two Dimensions Transitivity Within Dimension

21. Same Potential Issue With College Choice Simmons ≻ BU BU ≻ Northeastern Northeastern ≻ Simmons

22. Most Real-World Decisions Are Like This What Can We Do? (besides flip a coin)

23. Multi-Dimensional Scaling Discover relationships from comparisons: LA-NY > LA-Denver LA-Atlanta > Seattle-SF

24. Multi-Dimensional Scaling

25. Repertory Grid (Kelly, 1955) Gather a set of schools you think you might be interested in Enumerate all possible triples # Schools # Triples 31 43 56 610

26. Next Split each triple based on “feel” or intuition - whatever comes naturally. Define the way members of the pair are similar (and why they make a pair) and how the third is different. Example: BU, Simmons, Northeastern BU, NEU vs SimmonsLarge vs. Small

27. Repertory Grid (Kelly, 1955) Construct a matrix of comparisons: BUWheelockSimmonsHarvardNEU Size: Large vs Small 101 Co-ed vs. women 00100 Focus: Research vs Teaching 10011 Faculty: Brilliant vs Ordinary 00110 Good food vs. bad 00111

28. Repertory Grid (Kelly, 1955) Construct a matrix of comparisons: BUWheelockSimmonsHarvardNEU Size: Large vs Small 10011 Co-ed vs. women 00100 Focus: Research vs Teaching 10011 Faculty: Brilliant vs Ordinary 00110 Good food vs. bad 00111

29. Repertory Grid (Kelly, 1955) Sort the Matrix by Element (School) putting similar together BUNEUHarvardWheelockSimmons Size: Large vs Small 11100 Co-ed vs. women 00001 Focus: Research vs Teaching 11100 Faculty: Brilliant vs Ordinary 00101 Good food vs. bad 01101

30. Repertory Grid (Kelly, 1955) Sort the Matrix by Construct (Attribute) putting similar together BUNEUHarvardWheelockSimmons Size: Large vs Small 11100 Focus: Research vs Teaching 11100 Co-ed vs. women 00001 Faculty: Brilliant vs Ordinary 00101 Good food vs. bad 01101

31. Results BU and NEU are nearly identical; further examination may be necessary. Size and Research are equated - should they be or is this a bias? Double counting this influence? Which constructs are most important to you? BUNEUHarvardWheelockSimmons Size: Large vs Small 11100 Focus: Research vs Teaching 11100 Co-Ed vs. Women 10011 Faculty: Brilliant vs Ordinary 00101 Good food vs bad 01101

32. What College Is Best For You?

33. Simmons! What College Is Best For You?