Lecturing (leading a class, giving a talk, etc.)

1. Lecturing(leading a class, giving a talk, etc.) Kari Lock Morgan STA 790: Teaching Statistics 10/3/12

2. It’s not what you teach, it’s what they learn

3. It’s What They Learn • It doesn’t matter what or how much you cover if they aren’t paying attention or don’t understand • Always keep your focus on the students – are they with you? Do they seem to be getting it? • Focus on getting them to really learn what you do cover, not on getting through as much material as possible • Make them think during class

4. Get them Thinking • Ask them questions, get them involved and invested in the material • Ask questions that either • are clear and have specific answers • are open-ended and have a variety of possible responses

5. The Gold Standard • Randomized experiments are the “gold standard” for estimating causal effects • WHY? • They yield unbiased estimates • They eliminate confounding factors

6. R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R Randomize R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R R

7. Covariate Balance - Gender • Suppose you get a “bad” randomization • What would you do??? 5 Females, 15 Males 12 Females, 8 Males 15 Females, 5 Males 8 Females, 12 Males

8. Suppose you get a “bad” randomization and notice it before the experiment takes place. What would you do? Conduct the experiment as is Rerandomize

9. Start with Motivation • Why is what you are teaching important for the students to know? • Get them curious, and get them to want to understand what you are teaching • Depending on the class and topic, this may or may not use real data

10. Mind-Set Matters • In 2007, Dr. Ellen Langer tested her hypothesis that “mind-set matters” with a randomized experiment • She recruited 84 maids working at 7 different hotels, and randomly assigned half to a treatment group and half to control • The “treatment” was simply informing the maids that their work satisfies the Surgeon General’s recommendations for an active lifestyle • Crum, A.J. and Langer, E.J. (2007). “Mind-Set Matters: Exercise and the Placebo Effect,” Psychological Science, 18:165-171.

11. Mind-Set Matters p-value = .01 p-value = .001

12. Use Visuals • Often, visuals are much easier to understand than text • Flowcharts are a great way to enforce conceptual understanding of a procedure

13. Collect covariate data Specify criteria determining when a randomization is unacceptable; based on covariate balance 1) Randomize subjects to treated and control (Re)randomize subjects to treated and control 2) RERANDOMIZATION Check covariate balance acceptable unacceptable Conduct experiment 3) Analyze results (with a randomization test) 4)

14. Confidence Intervals Sample Sample Sample Sample Sample Sample Confidence Interval statistic ± ME Population . . . Margin of Error (ME) (95% CI: ME = 2×SE) Sampling Distribution Calculate statistic for each sample Standard Error (SE): standard deviation of sampling distribution

15. Have them discuss possibilities • Sometimes, you can have students discuss possibilities before you give them the answer • Decision: have them read before or after class?

16. Criteria for Acceptable Balance We use Mahalanobis Distance, M, to represent multivariate distance between group means: Choose a and rerandomize when M > a

17. Make Connections • Try to connect new concepts back to what they already know • Mahalanobis distance is just the (scaled) test statistic for the multivariate t-test

18. Distribution of M pa = Probability of accepting a randomization RERANDOMIZE Acceptable Randomizations

19. Covariates After Rerandomization Theorem: If nT = nC, the covariate means are normally distributed, and rerandomization occurs when M > a, then and

20. How can we make this more clear? • Pictures/visuals • Concrete examples • Special cases • Ask students questions to gauge understanding

21. Variance Reduction

23. Covariate Variance Reduction • In the maids example: • 10 covariates (k = 10) • pa= .001 • Want a such that P(210 < a) = .001 => a = 1.48

24. If the acceptance probability (pa) is increased, vawill… Increase Decrease

25. Covariate Variance Reduction

26. Covariate Variance Reduction

27. Estimated Treatment Effect After Rerandomization Theorem: If nT = nC , the covariate means are normally distributed, and rerandomization occurs when M > a, then and where R2 is the coefficient of determination (squared canonical correlation).

28. Outcome Variance Reduction Difference in Outcome Means va

29. Outcome Variance Reduction Outcome: Weight Change R2 = .1 Variance Reduction = 1 – (1 – va)R2 = 1 – (1 – .12)(.1) = .91 Outcome: Change in Diastolic Blood Pressure R2 = .64 Variance Reduction = 1 – (1 – va)R2 = 1 – (1 – .12)(.64) = .44 Equivalent to increasing the sample size by 1/.44 = 2.27

30. Use Examples! • Examples make everything more clear • Often, it’s easiest to start with a specific example to help understanding, then generalize • Choose examples that are interesting or relevant to the students • Examples solidify abstract concepts. • Everything should be illustrated with an example

31. Key Points • What are the key points you want your students to get during the lecture? • Make sure they learn these points, and fill in around this as needed • Don’t allow yourselves to get sidetracked too far from the point

32. Preparation!!! • Make sure you take the time to prepare your lectures in advance • Save time for finding interesting data/examples, making helpful visuals, etc. • Make sure everything you say is accurate • Think hard about ordering, where examples could be helpful, etc. • Keep time in mind

33. Time Management • Perhaps have a couple of different endpoints • End with an activity that could take as long as needed • Err on the side of having to explain things a bit more, rather than having to rush through important material

34. Note Taking • Make sure students will have enough details in their notes • If using the board, don’t just verbally say important information… students will need to see it when studying

35. Powerpoint or Board? • Which is better for lecturing? • It depends on your style… both have pros and cons

36. PowerPoint sound effects color animations graphics Allows seamless integration of technology Allows you to have continuous eye contact with your students Forces you to fully prepare in advance Frees students to thinkabout what you are saying rather than frantically copying it all down Lets you use

37. Blackboard When you have your text already typed on PowerPoint it’s easy to just read the slides and go too fast and entirely lose the attention of the students who don’t have to pay attention anyway because the notes are all online for them to go back to and look at later if they need them… Forcing the students to take notes ensures that they continue to pay attention and don’t fog out “The only way to keep the students engaged is to be engaged myself”

38. Powerpoint or Board? People have many different strategies for keeping students engaged… experiment and find what works for you It’s often not what you do, but how you do it