1. Statistic for the day: Payment that 5 former employees of Du Pont in 1988 demanded for keeping the formula for Lycra secret: $10,000,000 Assignment: Read Chapter 5, Do exercises 7, 8, 10, 13 Source: Du Pont These slides were created by Tom Hettmansperger and in some cases modified by David Hunter

2. The Gallup Poll is a good poll because: a. It is a random sample of the population b. It takes a large sample. c. It is done over the telephone. d. It is the oldest polling organization.

3. Recall the Literary Digest Poll of 1936 (page 65 of the text) A really bad example: The Hite Report: Women and Love. 1.100,000 questionnaires mailed out 2.4.5% response rate 3.Anger of women was one main theme but angry women are more likely to respond.

4. Comparisons Randomized Experiments Observational Studies EXPLANATORY VARIABLE says which population we sampled from. RESPONSE VARIABLE says what we measured or counted.

5. Suppose we design a study to compare the SAT scores of the College of Liberal Arts and the College of Education. We want to see if we can claim there is a significant difference. We have a 1.Observational Study 2.Randomized Experiment What are the response and explanatory variables?

6. Suppose your roommate is part of a comparative study to see if Vitamin C is effective at reducing the effects of a head cold. Do you think the study is a 1.Observational Study 2.Randomized Experiment What are the response and explanatory variables?

7. The key to a good observational study or a good randomized experiment is RANDOMIZATION in both cases. In observational studies we need a random sample from each population. In randomized experiments we must randomize the subjects to the different treatments (or treatment and control groups).

8. Randomized Experiment Associated concepts and ideas: Control group (provides a benchmark) Blinding: single or double (reduce bias) Placebo (benchmark, blinding) Confounding (a lurking third variable) Pairing or blocking (reduces noise in data)

9. Research Question: Does alcohol really reduce reaction time? Experiment: A short obstacle course was set up. Randomization: 50 student volunteers were randomly divided into two groups of 25 each: The treatment group drank 2 beers as quickly as theyThe treatment group drank 2 beers as quickly as they could tolerate. The control group drank two 12 ounce glasses of colaThe control group drank two 12 ounce glasses of cola Response variable: the time required to complete the course. (The measurement) Explanatory variable: whether the subject is in the treatment or the control group.

10. Yes, to gauge how fast someone can get through the course. What about blinding? Useful here to reduce measurement bias. (Who’s blinded?) Why a placebo? Do we really need one? Yes, since drinking 24 ounces might affect time. Confounding is an issue in observational studies. Randomization to treatment and control eliminates it in randomized experiments. What about pairing or blocking? Could it help here? Yes, if say women and men differ in their response to alcohol. For example size (weight) may be a factor. Why a control group? Do we need one?

11. If we get the above data, what can we say? Is there a (statistically) significant difference?

12. Boxplots sometimes show differences better than histograms. But could the difference just be due to chance?