Agenda

1. Agenda • Sampling • probability sampling • nonprobability sampling • External validity

2. Sampling • Drawing a subgroup from a population (vs. Census)

3. Students registered in FAMR 380 fall ’00 All registered HI voters in Sept. 2000 All Adidas shoes made in 1999 Everyone in class today Registered voters reached by random-digit dialing on 9/14/00 who answered the survey Every 2,000th pair produced at each plant PopulationSample

4. What is a good sample? • A sample that resembles the population in characteristics • (arepresentative sample)

5. Representativeness Sample Population

6. 40% Males 40% Males 60% Females 60% Females Representativeness Sample Population

7. 70% Satisfied 70% Satisfied 30% Dissatisfied 30% Dissatisfied Statistics Parameter Representativeness Sample Population

8. Why Representative Sample? • If characteristics of the sample is similar to the population, the statistics of sample are likely to be similar to the parameters

9. Let’s Think … • Research question: How do UH students utilize campus facilities? • Population: UH Students • Sample size: 200 • How will you sample? • How can you maximize representativeness of your sample?

10. Random Sampling • Gives everybody in the population an equal chance to be selected as a participant in the sample • Requires the list of everybody in the population

11. Population of 40: 25% 25% 50% Sample A Sample B Sample C Sample D SIMPLE RANDOM SAMPLE Sample of 4 : Each person 1/10 chance

12. Systematic Random Sampling • Pick up every ‘n’th subjects • Sensitive to the way the list is ordered

13. Population of 40: 25% 25% 50% Sample B Sample A SYSTEMATIC SAMPLE For a sample of 4, Take every 10th one

14. Stratified Random Sampling • Divide the population into groups (strata) • Select subject randomly from the stratum • Then proportion of groups in the sample is equal to proportion of groups in population

15. Population of 40: 25% 25% 50% STRATIFIED RANDOM SAMPLE Stratify (layer, category) by color Stratified random sample of 4: Randomly pick from each strata to maintain 25%,25%, 50% balance

16. Cluster Sampling • Sample a ready-made group within the population (cluster) assuming it has a similar composition to the population • Example: Third grade classrooms

17. Probabilty sample • Know exact chance of being included BEFORE participant is picked • E.g., 1 in 100, .003%, etc. • Need # in the population, • # in sample Non-probabilty Sample • DON’T know each participant’s chance of being picked

18. Simple random Systematic random Stratified random Cluster Each member of the population has a specifiable probability of being chosen Population info available Convenience Snowball Purposive Quota We don’t know the probability of a specific member of the population being chosen Population info not available Probability vs. Non-probability Probability Sampling Non-probability Sampling

19. Representativenss & Generalizability • Representativeness = Resembles population characteristics • Generalizability = Able to generalize the results of your study to the whole population • High representativeness = High generalizability • Probability sampling allows higher representativeness than non-probability

20. Non-probability Sampling

21. Convenience Sampling • Get available people in the population • Low representativeness / generalizability

22. Snowball Sampling • Obtain participants through a chain of personal networking-referrals • Useful to locate the ‘hidden’ or ‘difficult to recruit’ population • Low representativeness / generalizability

23. Quota Sampling • Predetermine the proportion of groups in the sample • e.g., male 50%, female 50% • e.g., clinical trials-drug research, etc.

24. Purpose of Quota Sampling • 1: To ensure that the sample reflects the proportion of the group in the population • 2: To secure enough numbers of group members for analysis • If you set quota for purpose 2, your sample may not reflect the population as a whole

25. Purposive Sampling • Obtain most informed / most ‘typical’ participants • “Judgmental sampling” • High quality of information from each participanta • Low representativeness / generalizability • Quality of sample depends on researcher’s ability to identify group to be studied

26. Why is sampling important? • Usually want to talk about a POPULATION • Easier to get a sub-set of the population (SAMPLE) • In a good sample • Results from a good sample should match the parent population (REPRESENTATIVE) • Participants should be chosen without bias (RANDOM) • This allows you to GENERALIZE the results-- what holds for the sample should also hold for the larger group

27. External Validity • Degree that results can be extended beyond the limited research setting • Extent findings can be generalized to others • Based on sample ( rats, college students, whites, males, lab setting)

28. External validity ? • Will the findings from this study likely be found • When other individuals are studied? • Volunteers / non-volunteers, • Gender • Under other conditions? • In other settings?

29. Psychology • The study of college sophomores • People in general? • College students - intelligent, high cognitive skills, young, developing sense of self-identity, social and political attitudes in state of flux, need for peer approval, unstable peer relationships (Cozby, 2001).

30. External validity • Related to sample and sampling technique

31. I hope you have a great day! A.C.A.