Sampling

1. Sampling Chapter Six

2. Sampling Chapter Six

3. What is a Sample? • Sampling is the process of selecting a number of individuals from a population, preferably in a way that the individuals are representative of the larger group from which they were selected. • A sample is any group on which information is obtained.

4. Defining the Population • A population refers to all the members of a particular group. • The first task in selecting a sample is to define the population of interest. • In Educational Research, the population of interest is a group of persons who possess certain characteristics. • A target population is the actual population that the researcher would like to generalize. • Considered rarely available • The accessible population would be the group that is available (realistic choice)

5. Representative vs. Non-representative Samples (Fig. 6.1)

6. Two Main Types of Sampling • Sampling may be either random or non-random • Random sampling is a method of selecting subjects from a population by chance, so that biases do not alter the sample. • The 3 most common ways of obtaining this type of sample are: • Simple Random Sampling • Stratified Random Sampling • Cluster Sampling

7. Part of a Table of Random Numbers (Table 6.1) • 011723 223456 222167 032762 062281 565451 • 912334 379156 233989 109238 934128 987678 • 086401 016265 411148 251287 602345 659080 • 059397 022334 080675 454555 011563 237873 • 666278 106590 879809 899030 909876 198905 • 051965 004571 036900 037700 500098 046660 • 063045 786326 098000 510379 024358 145678 • 560132 345678 356789 033460 050521 342021 • 727009 344870 889567 324588 400567 989657 • 000037 121191 258700 088909 015460 223350 • 667899 234345 076567 090076 345121 121348 • 042397 045645 030032 657112 675897 079326 • 987650 568799 070070 143188 198789 097451 • 091126 021557 102322 209312 909036 342045

8. Simple Random Sampling • A Simple Random Sampling is a sample selected from a population in such a manner that all members have an equal chance of being selected • If the sample is large, it is the best method to obtain a sample representative of the population from which it has been selected • The larger the sample size, the more it is likely to represent the population • Any differences that occur are the result of chance rather than bias on the part of the researcher • Disadvantages of this method are: 1) the difficulty of performing the sampling and, 2) this method does not ensure that subgroups are present in the sampling in the same proportion as they are in a population

9. Stratified Random Sampling • A Stratified Random Sampling is a sample selected so that certain characteristics are represented in the sample in the same proportion as they occur in the population • The term strata refers to sub-groups • The advantage of stratified random sampling is that it increases the likelihood of representation, especially if the sample size is small • It virtually ensures that any key characteristics of individuals in the population are included in the same proportions in the sample size • The disadvantage is that it requires still more effort on the part of the researcher

10. Selecting a Stratified Sample (Figure 6.2)

11. Cluster Random Sampling • A Cluster Random Sampling is a sample obtained by using groups as the sampling unit (cluster), rather than individuals • There are instances where it is not possible to select a sample of individuals from a population • This is considered more effective with large numbers of clusters • Advantages include more efficient and easier to implement in schools • Its disadvantage is that there is a great chance of selecting a sample that is not representative of the population

12. Random Sampling Methods (Figure 6.3)

13. Two-Stage Random Sampling • This method selects groups randomly and then chooses individuals randomly from these groups. • This becomes a combination of a cluster random sampling with individual random sampling. • Considered less time consuming but allows for a good representation of the groups at random.

14. Nonrandom Sampling Methods • There are 3 main types of nonrandom sampling methods used in Educational Research • A Systematic Sample is a sample obtained by selecting every nth name in a population • A Convenience Sample is any group of individuals that is conveniently available to be studied • Are not considered representative of the population and should be avoided, if possible • A Purposive Sample is a sample selected because the individuals have special qualifications of some sort, or because of prior evidence of representation • Personal judgment is used for selection purposes • A major disadvantage is that the researcher’s judgment could be in error

15. Convenience Sampling (Figure 6.4)

16. Nonrandom Sampling Method (Figure 6.5)

17. Sample Size • The question remains as to what constitutes an adequate sample size. • Samples should be as large as a researcher can obtain with a reasonable expenditure of time and energy. • The recommended minimum number of subjects are as follows for the following types of studies: • 100 for a Descriptive Study • 50 for a Correlational Study • 30 in each group for Experimental and Causal-Comparative Study The use of 15 subjects per group should probably be replicated

18. External Validity, a.k.a. Generalizability • The whole notion of science is built on generalizing. • External Validity refers to the extent that the results of a study can be generalized from a sample to a population. • Population generalizability is the degree to which a sample represents the population of interest. • Obtaining a representative sample becomes very important • Ecological generalizability refers to the extent to which the results of a study can be generalized to conditions or settings other than those that prevailed in the study.

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