Sampling

1. Sampling 6

2. Sampling

3. What Is a Sample? One of the most important steps in the research process is to select the sample of individuals who will participate (be observed or questioned) as a part of the study. Sampling refers to the process of selecting these individuals. A �sample� in a research study refers to any group on which information is obtained. The larger group to which one hopes to apply the results is called the population.

4. Samples and Populations When it is possible, researchers would prefer to study the entire population in which they are interested. Usually, however, this is difficult to do. Most populations of interest are large, diverse, and scattered over a large geographic area. Finding, let alone contacting, all members can be time-consuming and expensive. For that reason, of necessity, researchers often select a sample to study. A population can be any size and it will have at least one (and sometimes several) characteristic(s) that sets it off from any other population. Notice that a population is always all of the individuals who possess a certain characteristic (or set of characteristics). Fraenkel p. 97

5. Samples and Populations (cont�d) In educational research, the population of interest is usually a group of persons (students, teachers, or other individuals) who possess certain characteristics. In some cases, however, the population may be defined as a group of classrooms, schools, or even facilities. Target population � the actual population to which a researcher would like to generalize � rarely available �ideal choice Accessible population � the population to which a researcher is able to generalize �realistic choice

6. Random versus Nonrandom Sampling Random sampling � its intent is to select a representative sample from the population

7. Representative vs. Non-representative Samples

8. Random Sampling Methods Simple Random Sample � a sample in which each and every member of the population has an equal and independent chance of being selected

9. Part of a Table of Random Numbers (Table 6.1)

10. Random Sampling Methods Stratified Random Sample � a process in which certain subgroups, or strata, are selected for the sample in the same proportion as they exist in the population This requires the researcher to know some information about the people in the population

11. Selecting a Stratified Sample (Figure 6.2)

12. Random Sampling Methods (cont�d) Cluster Random Sampling � the selection of groups, or clusters, of subjects rather than individuals Two-Stage Random Sampling � a combination of cluster random sampling with individual random sampling

13. Random Sampling Methods (Figure 6.3)

14. Nonrandom Sampling Methods Systematic Sampling � every nth individual in the population list is selected for inclusion in the sample If the initial individual is selected randomly then this method is technically known as systematic sampling with a random start. The sampling interval is the distance in the list between each of the individuals selected. It is determined by dividing the population size by the desired sample size. The sampling ratio is the proportion of the population that is selected for the sample. It is determined by dividing the sample size by the population size.

15. Nonrandom Sampling Methods (cont�d) Convenience Sampling � a group of individuals who (conveniently) are available for study. In general, these samples cannot be considered representative of any population and should be avoided if at all possible. If this is the only type of sample the researcher can use, then they should be extremely careful to include demographic information and other characteristics of the sample that was studied. The study should also be replicated with a number of similar samples to decrease the likelihood that the results obtained were simply a one-time occurrence.

16. Convenience Sampling (Figure 6.4)

17. Nonrandom Sampling Methods (cont�d) Purposive Sampling � a sampling method in which the researcher selects the sample based on previous knowledge of a population. This is different from convenience sampling in that researchers do not simply study whoever is available, but use their judgment to select a sample that they believe, based on prior information, will provide the data they need.

18. Nonrandom Sampling Method (Figure 6.5)

19. Sample Size A sample should be as large as the researcher can obtain with a reasonable expenditure of time and energy.

20. External Validity: Generalizing from a Sample Both the nature of the sample and the environmental conditions � the setting - within which a study takes place must be considered in thinking about generalizability. The extent to which the results of a study can be generalized determines the external validity of the study. Population generalizibility refers to the degree to which a sample represents the population of interest. If the results of a study only apply to the group being studied, and if that group is fairly small or is narrowly defined, the usefulness of any findings is seriously limited. This is why trying to find a representative sample is so important.

21. External Validity: Generalizing from a Sample (cont�d) One aspect of generalizability that is often overlooked in �methods� or �treatment� studies is that which pertains to the teachers, counselors, administrators, or others who administer the various treatments. A study that randomly selects students but not teachers is only entitled to generalize the outcomes to the population of students - if taught by the same teachers. To generalize to other teachers, the sample of teachers must also be selected randomly and must be sufficiently large. The best sampling plan is of no value if information is missing on a sizable portion of the initial sample.

22. External Validity: Generalizing from a Sample (cont�d) Do researchers always want to generalize? No, not if the results of an investigation are of interest only as applied to a particular group of people at a particular time, and where all of the members of the group are included in the study. Random sampling is sometimes not feasible which makes much of the research in education subject to criticism. Replication of a study can give a researcher more confidence about generalizing their findings despite the lack of a random sample.

23. Ecological Generalizability Ecological generalizability refers to the degree to which results of a study can be extended to other settings or conditions. Researchers must make clear the nature of the environmental conditions � the setting - under which a study takes place. Only when outcomes have been shown to be similar through replication across specific environmental conditions can we generalize across these conditions.

24. Population as Opposed to Ecological Generalizing (Figure 6.6)