Research Methods Chapter 5

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1

Population

the entire set of individuals of interest to a researcher. although the entire population usually does not participate in a research study, the results from the study are generalized to the entire population

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sample

set of individuals selected from a population and usually is intended to represent the population in a research study

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target population

the group defined by the researcher's specific interests

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representativeness

of a sample refers to the extent to which the characteristics of the sample accurately reflect the characteristics of a population

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representative sample

sample with the same characteristics as the population

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biased sample

a sample with different characteristics from those of the population

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selection bias or sampling bias

occurs when participants or subjects are selected in a manner that increases the probability of obtaining a biased sample

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sampling

is the process of selecting individuals to participate in a research study

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probability sampling

the entire population is known, each individual in the population has a specifiable probability of selection, and sampling occurs by a random process based on the probabilities

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random process

is a procedure that produces one outcome from a set of possible outcomes. must be unpredictable each time, and the process must guarantee that each of the possible outcomes is equally likely to occur

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nonprobability sampling

the population is not completely known, individual probabilities cannot be known, and the sampling method is based on factors such as common sense or ease, with an effort to maintain representativeness and avoid bias

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Simple Random Sampling

obtained using a random process to select participants from a list consisting the total population. each individual has an equal and independent chance of selection

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Systematic Sampling

obtained by selecting every nth participant from a list containing the total population, after a random start

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Stratified Random Sampling

obtained by dividing the population into subgroups (strata) and then randomly selecting equal numbers from each of the subgroups

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Proportionate Stratified Random Sampling

obtained by subdividing the population into strata and then randomly selecting from each stratum a number of participants so that the proportions in the sample correspond to the proportions in the population

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Cluster Sampling

instead of selecting indivduals, a sample is obtained by randomly selecting clusters from a list of all the clusters that exist within the population

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Convenience Sampling

obtained by selecting individual participants who are easy to get

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Quota Sampling

obtained by identifying subgroups to be included, then establishing quotas for individuals to be selected through convenience from each subgroup