Summary of Chapter 5
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| Sampling | process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected
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| Purpose of sampling | gain information about a larger population
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| Simple random sampling | process of selecting a sample in such a way that all individuals in the defined population have an equal and independent chance of selection for the sample
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| Random sampling | involves defining the population, identifying each member of the population, and selecting individuals for the sample on a completely chance basis. Usually a table of random numbers is used to select the sample.
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| Stratified sampling | process of strategically selecting a sample in such a way that guarantees desired representation of relevant subgroups within the sample
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| Stratified sampling | can be used to select proportional or equal sized samples from each of a number of subgroups
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| The steps in stratified sampling | similar to those in random sampling except that selection is from subgroups in the population rather than the population as a whole.
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| Cluster Sampling | sampling in which groups not individuals are randomly selected
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| Clusters | can be communities, states, school districts
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| The steps in cluster sampling are | similar to those in random sampling except that the random selection of groups (clusters) in involved
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| Cluster sampling | often involves selection of clusters within clusters (e.g. districts in a state, then schools in a district) in a process known as multistage sampling
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| Systematic sampling | sampling in which every Kth individual is selected from a list of all members in the population.
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| K | variable determined by dividing the number of individuals on the list by the number of subjects desired for the sample.
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| Sampling error | beyond the control of the researcher and occurs as part of random selection procedures
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| Sampling bias is systematic | generally the fault of the researcher
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| Major source of bias | the use of nonrandom sampling techniques
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| Any sampling bias | present in a study should be fully described in the final research report
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| Three types of nonrandom sampling | 1. Convenience sampling
2. Purposive sampling
3. Quota sampling
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| Convenience sampling | involves selecting whoever happens to be available
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| Purposive sampling | involves selecting a sample the researcher believes to be representative of a given population
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| Quota sampling | involves selecting a sample based on exact numbers or quotas of persons of varying characteristics
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| Qualitative sampling | process of selecting a small number of individuals who will contribute to the researcher's understanding of the phenomenon under study
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| Qualitative researcher | often deals with small, purposive samples
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| Purposive sampling | approaches include intensity sampling, homogenous sampling, criterion sampling, snowball sampling and random sampling
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| Two general indicators used to determine whether a sample is of sufficient size | representativeness and redundancy of information
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| Intensity sampling | Compare differences of two or more levels of the topic (e.g., good vs bad students); select two groups of about 20 participants from each of the two levels
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| Homogenous sampling | select a small group of participants who fit a narrow, homogenous topic; collect data from the chosen participants
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| Criterion sampling | identify participants who meet the defined criterion; select a group of five or so participants and collect data from them.
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| Snowballing sampling | decide how many participants are needed, let initial participants recruit additional participants that fit the researcher's requirements until the desired number is reached.
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| Random purposive sampling | Given a pool of participants, decide how many of them can reasonably be dealt with in the study, and randomly select this number to participate. (this strategy is intended to deal with small samples)
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