1. Agresti/Franklin Statistics, 1 of 56 Chapter 4 Gathering data Learn …. How to gather “good” data About Experiments and Observational Studies

2. Agresti/Franklin Statistics, 2 of 56  Section 4.1 Should We Experiment or Should we Merely Observe?

3. Agresti/Franklin Statistics, 3 of 56 Population, Sample and Variables Population: all the subjects of interest Sample: subset of the population - data is collected on the sample Response variable: measures the outcome of interest Explanatory variable: the variable that explains the response variable

4. Agresti/Franklin Statistics, 4 of 56 Types of Studies Experiments Observational Studies

5. Agresti/Franklin Statistics, 5 of 56 Experiment A researcher conducts an experiment by assigning subjects to certain experimental conditions and then observing outcomes on the response variable The experimental conditions, which correspond to assigned values of the explanatory variable, are called treatments

6. Agresti/Franklin Statistics, 6 of 56 Observational Study In an observational study, the researcher observes values of the response variable and explanatory variables for the sampled subjects, without anything being done to the subjects (such as imposing a treatment)

7. Agresti/Franklin Statistics, 7 of 56 Example: Does Drug Testing Reduce Students’ Drug Use? Headline: “Student Drug Testing Not Effective in Reducing Drug Use” Facts about the study: 76,000 students nationwide Schools selected for the study included schools that tested for drugs and schools that did not test for drugs Each student filled out a questionnaire asking about his/her drug use

8. Agresti/Franklin Statistics, 8 of 56 Example: Does Drug Testing Reduce Students’ Drug Use?

9. Agresti/Franklin Statistics, 9 of 56 Example: Does Drug Testing Reduce Students’ Drug Use? Conclusion: Drug use was similar in schools that tested for drugs and schools that did not test for drugs

10. Agresti/Franklin Statistics, 10 of 56 Example: Does Drug Testing Reduce Students’ Drug Use? What were the response and explanatory variables?

11. Agresti/Franklin Statistics, 11 of 56 Example: Does Drug Testing Reduce Students’ Drug Use? Was this an observational study or an experiment?

12. Agresti/Franklin Statistics, 12 of 56 Advantages of Experiments over Observational Studies We can study the effect of an explanatory variable on a response variable more accurately with an experiment than with an observational study An experiment reduces the potential for lurking variables to affect the result

13. Agresti/Franklin Statistics, 13 of 56 Experiments vs Observational Studies When the goal of a study is to establish cause and effect, an experiment is needed There are many situations (time constraints, ethical issues,..) in which an experiment is not practical

14. Agresti/Franklin Statistics, 14 of 56 Good Practices for Using Data Beware of anecdotal data Rely on data collected in reputable research studies

15. Agresti/Franklin Statistics, 15 of 56 Example of a Dataset General Social Survey (GSS): Observational Data Base Tracks opinions and behaviors of the American public A good example of a sample survey Gathers information by interviewing a sample of subjects from the U.S. adult population Provides a snapshot of the population

16. Agresti/Franklin Statistics, 16 of 56  Section 4.2 What Are Good Ways and Poor Ways to Sample?

17. Agresti/Franklin Statistics, 17 of 56 Setting Up a Sample Survey Step 1: Identify the Population Step 2: Compile a list of subjects in the population from which the sample will be taken. This is called the sampling frame. Step 3: Specify a method for selecting subjects from the sampling frame. This is called the sampling design.

18. Agresti/Franklin Statistics, 18 of 56 Random Sampling Best way of obtaining a representative sample The sampling frame should give each subject an equal chance of being selected to be in the sample

19. Agresti/Franklin Statistics, 19 of 56 Simple Random Sampling A simple random sample of ‘n’ subjects from a population is one in which each possible sample of that size has the same chance of being selected

20. Agresti/Franklin Statistics, 20 of 56 Example: Sampling Club Officers for a New Orleans Trip The five offices: President, Vice- President, Secretary, Treasurer and Activity Coordinator The possible samples are: (P,V) (P,S) (P,T) (P,A) (V,S) (V,T) (V,A) (S,T) (S,A) (T,A)

21. Agresti/Franklin Statistics, 21 of 56 The possible samples are: (P,V) (P,S) (P,T) (P,A) (V,S) (V,T) (V,A) (S,T) (S,A) (T,A) What are the chances the President and Activity Coordinator are selected? a. 1 in 5 b. 1 in 10 c. 1 in 2

22. Agresti/Franklin Statistics, 22 of 56 Selecting a Simple Random Sample Use a Random Number Table Use a Random Number Generator

23. Agresti/Franklin Statistics, 23 of 56 Methods of Collecting Data in Sample Surveys Personal Interview Telephone Interview Self-administered Questionnaire

24. Agresti/Franklin Statistics, 24 of 56 How Accurate Are Results from Surveys with Random Sampling? Sample surveys are commonly used to estimate population percentages These estimates include a margin of error

25. Agresti/Franklin Statistics, 25 of 56 Example: Margin of Error A survey result states: “The margin of error is plus or minus 3 percentage points” This means: “It is very likely that the reported sample percentage is no more than 3% lower or 3% higher than the population percentage” Margin of error is approximately:

26. Agresti/Franklin Statistics, 26 of 56 Be Wary of Sources of Potential Bias in Sample Surveys A variety of problems can cause responses from a sample to tend to favor some parts of the population over others

27. Agresti/Franklin Statistics, 27 of 56 Types of Bias in Sample Surveys Sampling Bias: occurs from using nonrandom samples or having undercoverage Nonresponse bias: occurs when some sampled subjects cannot be reached or refuse to participate or fail to answer some questions Response bias: occurs when the subject gives an incorrect response or the question is misleading

28. Agresti/Franklin Statistics, 28 of 56 Poor Ways to Sample Convenience Sample: a sample that is easy to obtain Unlikely to be representative of the population Severe biases my result due to time and location of the interview and judgment of the interviewer about whom to interview

29. Agresti/Franklin Statistics, 29 of 56 Poor Ways to Sample Volunteer Sample: most common form of convenience sample Subjects volunteer for the sample Volunteers are not representative of the entire population

30. Agresti/Franklin Statistics, 30 of 56 A Large Sample Does Not Guarantee An Unbiased Sample Warning: