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Figure 8.1 also lists various kinds of probability and nonprobability sampling. We discuss each kind of sampling later in this chapter. Probability versus nonprobability sampling Probability sampling methods rely only on random or chance selection. Only a carefully selected probability sample allows a researcher to generalize from sample results to the population from which the sample was selected. One of the four sampling methods we describe should meet about any sampling requirement you will face. Each method is based on chance and chance alone. No other consideration is allowed to affect who is included in the sample. Human choice or judgment is specifically ruled out. Once the chance process is started, the researcher accepts the resulting sample and makes no adjustments or other changes to make it come out any differently.  Figure 8.1. Decisions
regarding sampling
In contrast, nonprobability samples are selected by means other than chance, typically on some from of human choice or judgment. Respondents, for example, might be selected because they were friends or relatives or lived in easily accessible places. Any nonprobability sample has a serious limitation. There is no way to show that a nonprobability sample represents any population. A nonprobability sample is just a collection of some number of persons or other units and nothing more. This means that results from nonprobability samples cannot be safely generalized beyond the particular collection of persons from whom the data were collected. Use of probability samples avoids this limitation. By using chance, we eliminate any possible bias in the selection of respondents. When proper procedures are used, probability sampling gives the best assurance that the resulting sample represents the population from which it was selected. |