1. PRODUCING DATA

2. A look at your class The class survey The class survey

3. How Data are Obtained Observational Study –Observes individuals and measures variables but does not attempt to influence responses –Includes surveys and polls –E.g., Current Population SurveyCurrent Population Survey Experiment –Deliberately imposes some treatment on individuals in order to observe their responses –In medicine, this is often a clinical trialclinical trial –By controlling and isolating variables, an experiment can establish a causative relationship.

4. Nurses Health Study Large observational study begun in 1976 “One of the most significant studies ever conducted on the health of women.” Over 100,000 nurses aged 30 to 55 have been followed for more than 30 years Prospective study (versus retrospective) Questionnaires sent out every two years on many health and nutrition issues 90% response rate (that’s excellent!)

5. Nurses Health Study Although the nurses study is highly respected, much-cited and enormously useful, it has limitations Observational Study versus Experiment Nurses may not be representative of all women Read Hormone Studies: What Went Wrong? And An About-Face on Hormone Therapy.Hormone Studies: What Went Wrong?An About-Face on Hormone Therapy. Should women take hormone therapy drugs for severe post-menopausal symptoms? Nurses Health Study found a 61% decrease in heart disease risk among women who took Prempo, a widely- used hormone drug But another prominent study, the Women’s Health Initiative, found a 29% increase in heart disease risk

6. Sampling Goal: To get information about a population A good sample is representative of the population Statistical inference uses the information in a sample to draw conclusions about a population But, it only works if the sample is representative

7. Population individuals

8. List of Individuals 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Census 1 9 2 345 6 7 8 10 17 16 15 13 14 12 11 1 9 2 345 6 7 8 10 17 16 15 13 14 12 11 Census

9. Sampling Frame 1 9 2 345 6 7 8 10 17 16 15 13 14 12 11 List of Individuals 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Sample

10. Sample Survey Collect data Take measurements Compute statistics

11. Sampling – What can go wrong? A bad sampling design is one that consistently misrepresents the population Bias – the bane of the statistician Bias systematically favors some parts of the population over others in choosing the sample Some poor, and biased, sampling plans: –Convenience sampling –Voluntary response

12. Convenience Sampling Selecting individuals that are easiest to reach (e.g., our age-guessing experiment) Example: A researcher is using mice to study how a drug affects physical –Lab assistant reaches into a large cage to select the mice one at a time until 10 are chosen –Could this sample yield biased results?

13. Voluntary Response bias Allowing individuals to choose to be in the sample Internet polls are big culprits.Internet polls Dear Abby (advice columnist Ann Landers) once asked parents, “If you had it to do over again, would you have children?” Do you think responses were representative of public opinion? Over 100,000 people responded, and 70% answered “No”! A later survey, more carefully designed, showed 90% of parents are happy with their decision to have children

14. Random Sampling The antidote to bias is random sampling In simple random sampling, each individual in the population has the same chance of being chosen for the sample For a sample of size n, each group of n individuals in the population has the same chance of being the sample that is actually selected And using chance allows for quantitative methods (e.g., probability) to analyze the results and make inferences Some common methods of random selection: –Drawing names out of a hat –Table of random numbers (See Table A in the textbook) –Computer software

15. Simple Random Sampling Suppose we want to survey political attitudes among students at Carleton. Goal: Sample 20 students and ask them about politics What do you think of these sampling designs? –Choose 20 students at the library –Choose the first 20 students on an alphabetized master list –Choose every 90 th student on an alphabetized master list –Choose the first 20 students you meet –Choose 5 frosh at random, 5 sophomores at random, 5 juniors at random, and 5 seniors at random –Send out a campus wide e-mail and choose the first 20 who respond –Choose 20 random students in your dorm Which of these sampling designs do you think is the best?

16. How to choose a sample Humans are notoriously bad random number generators How good did you do? Class SurveyClass Survey Randomization is best way to eliminate bias and obtain a sample that is representative of the population In class, we’ll often use the Random number tableRandom number table A silly example: What % of this class are sophomores? Pick five students at random and find the sample percentage. Do itDo it What if I picked from the first row?