1. Counting in binary is as easy as 01 10 11.

2. What do you get when you cross a joke with a rhetorical question?

3. 3.1: Experiments, Good and Bad Statistics Chap 3: Designing Experiments

4. Emily Rosa’s 4 th Grade Science Project ABC Report Journal of American Medical Association

5. The Vocabulary of Experiments Response VariableMeasures an outcome or result of a study Explanatory VariableExplains or causes changes in the response variables -- Factors SubjectsThe individuals studied in an experiment – experimental units TreatmentAny specific experimental condition applied to the subjects.

6. Experiments vs Observational Study Experiments can give good evidence for causation.

7. Tennessee STAR Program The Tennessee STAR program was an experiment on the effects of class size. It has been called “one of the most important educational investigations ever carried out.” The subjects were 6385 students who were beginning kindergarten. Each student was assigned to one of three treatments: regular class (22-25 students) with one teacher, regular class with a teacher and a full-time teacher’s aide, and small class (13-17 students). These treatments are levels of a single factor (explanatory variable), the type of class. The students stayed in the same type of class for four years, then all returned to regular classes. In later years, students from the small classes had higher scores on standardized tests, were less likely to fail a grade, had better high school grades, and so on.

8. Confounding Lurking VariableHas an important effect on the relationship among the variables in a study but is not one of the explanatory variables Confounded VariablesVariables whose effects on a response variable cannot be distinguished from each other

9. Principles of Experimental Design 1.Control the effects of lurking variables on the response, most simply by comparing two or more treatments. 2.Replicate each treatment on many units to reduce chance variation in the results. 3.Randomize – use impersonal chance to assign experimental units to treatments.

10. Control Treatment → Observe response Minimize variability in the way the experimental units are obtained and treated.

11. Example Ability to grow in shade may help pines found in the dry forests of Arizona to resist drought. How well do these pines grow in shade? Investigators planted pine seedlings in a greenhouse in either full light, light reduced to 25% of normal by shade cloth, or light reduced to 5% of normal. At the end of the study, they dried the young trees and weighed them. Identify the experimental units, the factors, the treatments, and the response variables.

12. Replication Use enough subjects to reduce chance variation Randomization The rule used to assign the experimental units to the treatments

13. Example Does talking on a hands-free cell phone distract drivers? Outline of a randomized comparative experiment: Random allocation Group 1 20 students Group 2 20 students Treatment 1 Drive Treatment 2 Drive and talk Compare brake time

14. Randomized Comparative Experiments Randomization produces two groups of subjects that we expect to be similar in all respects before treatments are applied. Comparative design helps ensure that influences other than the cell phone operate equally on both groups. Therefore, differences in average brake reaction time must be due either to talking on the cell phone or to chance.

15. Example Does regularly taking aspirin help protect people against heart attacks? The Physicians’ Health Study looked at the effects of two drugs: aspirin and beta-carotene Subjects: 21,996 male physicians Two factors w/ two levels:Aspirin (yes/no) Beta-Carotene (yes/no)

16. Example (cont) On odd-numbered days, subjects took either a white tablet that contained aspirin or a placebo On even-numbered days, subjects took either a blue beta-carotene capsule or a placebo After several years, 239 of the placebo group but only 139 of the aspirin group had suffered heart attacks.

17. Statistical Significance An observed effect so large that it would rarely occur by chance.

18. Hawthorne Effect

19. Observational Studies can be valid Good studies are comparative We can often combine comparison with matching in creating a control group

20. Homework pp 150-151: 3.15, 17-21