Chapter 4

1. Chapter 4 Research Participants: Samples

2. Topics of Discussions • Sampling: Definition and Purpose • Definition of a population • Selecting a Random Sample • Simple Random Sampling • Stratified Sampling • Cluster Sampling • Systematic Sampling

3. Topics of Discussion (contd) • Determining Sample Size • Avoiding Sampling Error and Bias • Selecting a nonrandom sample • Sampling in Qualitative research

4. Sampling: Definition and Purpose • Sampling—a process of selecting a number of individuals for a study in a way that represents the larger group from which they were selected. • A sample represents the larger group—population • Purpose of sampling—to gain information about the population by using the sample • Generalizability—the degree to which the results of the sample maybe applicable to the entire population and situations. • Target population—population to which the researcher wants to generalize the results to. • Accessible population?

5. Selecting a Random Sample • A good sample is one that is representative of the population from which it was selected • Sampling techniques: • Random sampling—all individuals in the defined population have an equal and independent chance of being selected for the sample • Stratified Sampling—selection of a sample in ways where the identified subgroups are represented as in the target population. (104) eg. If population is 30% minority, sample should contain 30% minorities etc.

6. Cluster Sampling • Cluster sampling randomly selects groups, not individuals. • All members of selected groups have similar characteristics. • (Steps in cluster sampling—130) • Drawbacks—chances are greater of selecting a sample that is not representative of population.

7. Systematic Sampling • Not used often—sampling in which individuals are selected from a list by taking every Kth name. K=population/sample size • Random Sampling Strategies table -important to know—the advantages and disadvantages.

8. Determining Sample Size • Rule of Thumb—sample should be large enough to be generalizable to the entire population otherwise you cannot claim generalizability. • 30 participants minimum recommended • The larger the population, the smaller the percentage of population required. • See Table 4.2:sample sizes Vs Populations

9. Sampling Error and Bias • Sampling error—beyond the control of the researcher—reality of random sampling • Sampling bias-it is nonrandom and a fault of the researcher. EX: • Sampling bias affects the validity of the study

10. Non-Random Samples • Or Non-probability sampling—sampling methods that do not have random sampling at any stage of sample selection • Convenience sampling—includes whoever is available • Purposive sampling—judgement sampling—used often for qualitative studies • Quota sampling

11. Sampling in Qualitative Research • Purposive Sampling used. • Intensity sampling—permits study of different levels of the research topic within one group (diversity-good students, poor students etc) • Homogenous sampling-no diversity. Sample has similar characteristics • Snowball sampling—selecting few participants who identify other good participants • Random purposive sampling—selecting randomly from a purposive sample

12. Qualitative Sampling • Qualitative research uses sampling strategies that produce samples that are predominantly small and non random. • Keeps in line with QR’s emphasis on in-depth description of participants’ perspectives and context. • Purposive sampling ensures that the “best” participants are included.

13. Task 4: Choosing your sample • Define the population (size, relevant characteristics—age, ability, socioeconomic status • Procedural technique for selecting sample-what sampling techniques will you use (eg. Stratified-and how and why). • How will the sample be treated or be assigned to groups?