SUBJECTS AND SAMPLING

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# As

as

the larger population. The goal is to select a sample that will adequately represent the population, so that what is described in the sample will also be true of the population. The best procedure for selecting such a sample is to use probability sampling, a method of sampling in which the subjects are selected randomly in such a way that the researcher knows the probability of selecting each member of the population. Random selection implies that each member of the population as a whole or of subgroups of the population has a” equal chance of being selected. long the number of cases selected is large enough, it is likely that a very small percentage of the population, represented by the sample, will provide a” accurate description of the entire

Probablllty

sampling: Known Probability of selection from the population.

population.

It should be noted, however, that there is always some degree of

very

error in sampling, and that error must be considered in interpreting the results of the sample. In probability sampling this calculation can be made precisely with some statistical procedures. Consider a popula- tion of 1,000 third-graders, from which you will select randomly 5 per- cent, or 50, to estimate the attitudes of all the third-graders toward school. If the attitude score was 75 for the sample of 50 subjects, 75 can be used to estimate the value for the entire population of third-graders. However, if another sample of 50 students is selected, their score might

be a

little

different, say 73. Which one is more correct? Since all 1,000

students have not been tested to obtain the result we do not know for sure, but the results can be used to estimate the error in sampling. This is basically the technique that political polls follow when it is reported

that the vote is 45 percent ror in sampling.

+

# 3. The plus or minus 3 is the estimate of er-

There are many types of probability sampling procedures. You will probably encounter four types in educational research: simple random,

systematic, stratified, and cluster.

Simple Random Sampling In

simple

random

sampling evely

member

of the population has a” equal and independent chance of being se- lected for the sample. This method is often used with a small number in

the population, for example, putting the

names

or numbers of all popu-

Simple Each member

the population

random sampling:

of

has the same probability of being

selected.

lation members in a hat and drawing some out

as

the sample. If

way

member of the population can be assigned a different number, a table of random numbers can identify the population members that will make up the sample. This approach is not convenient if the population is large and not numbered. The most common way of selecting a ran- dom sample from a large population is by computer. There are com- puter programs that will assign numbers to each element in the popula- tion, generate the sample numbers randomly, and then print out the

names of the people corresponding to the numbers.