1. How can small samples represent large populations?
Probability Sampling
Nonprobability Sampling

2. Probability Sampling ASSUMES A NORMAL DISTRIBUTION OF THE POPULATION
Includes: random sampling, stratified sampling, cluster sampling, systematic sampling.

3. n>30 tends to reflect pop.
Random Sampling:
Each individual in the total population has equal chance of being selected.
n>30 tends to reflect pop.

4. Stratified Sampling:
Used to ensure that subgroups within the population are proportionally represented
Elmwood school contains many different ethnic groups: 33% Anglo, 28% Hispanic, 14% African American, 9% Japanese, 7% Korean, 3% Chinese, others 6%.
We decide ahead of time: randomly selected: 33 Anglos, 28 Hispanic, 14 African American, and so forth...

5. Random selection of already exiting groups.
Cluster Sampling:
Random selection of already exiting groups.
Elmwood School District has 10 fourth grade classes. We want to teach a new method of math. Randomly select four classes from the district who will learn the new math. May not be as representative of population; however may be more convenient to use.

6. Systematic Sampling:
Obtaining a sample by selecting every nth name from a master list of the population.
From a list name is randomly chosen; every nth (ie. 10th, 100th) name is chosen. Often more convenient than random.

7. Nonprobability Sampling:
Acknowledges that the sample may not be representative of the population.
1. Convenience Sampling
2. Judgmental Sampling
3. Quota Sampling

8. Convenience Sampling:
Uses groups that are simply available.
ie. Researchers using their own classes or selected classes of their peers.
Choosing a group of patients purely because they are in your clinic.

9. Purposive Sampling. Selecting certain segments of a population.
Judgmental Sampling:
Purposive Sampling. Selecting certain segments of a population.
ie. Researching lifestyle of 10 deviant students with a history of chronic misbehavior in school. More appropriate for qualitative than quantitative research.

10. Quota Sampling:
Used when an investigator wants to conduct research applicable to the population, but is unable to draw a sample from the pop.
ie. Want to examine the educational backgrounds of Elmwood Schools parents. Given existing information we could contact parents that are believed to represent the groups in the population regarding age, socio-economic status, gender, and so forth...

11. How many Subjects are enough?
Correlational research: > 30.
Experimental Research: > 15 per group.
Those involving intact classrooms: > 5 classrooms per research treatment.