Chapter 15
Learning Objective 1
Explain the difference between a census and a sample.
Taking information from or about every member of a target population is called a census. A sample is a portion of the population taken from the larger group.
Learning Objective 2
List the six steps researchers use to draw a sample of a population.
The six steps researchers use in drawing a sample are (1) define the target population, (2) identify the sampling frame, (3) select a sampling procedure, (4) determine the sample size, (5) select the sample elements, and (6) collect the data from the designated elements.
Learning Objective 3
Explain the difference between a parameter and a statistic.
A parameter is a characteristic of the population; if it were possible to take measures from all population members without error, we could arrive at the true value of a parameter. A statistic is a characteristic or measure of a sample; statistics are used to estimate population parameters.
Learning Objective 4
Explain the difference between a probability sample and a nonprobability sample.
In a probability sample, each member of the target population has a known, nonzero chance of being included in the sample. The chances of each member of the target population being included in the sample may not be equal, but everyone has a known probability of inclusion. With nonprobability samples, on the other hand, there is no way of estimating the probability that any population element will be included in the sample. Thus, there is no way of ensuring that the sample is representative of the target population. All nonprobability samples rely on personal judgment at some point in the sample selection process.
Learning Objective 5
Explain what a judgment sample is and describe its best use and its hazards.
In a judgment sample, sample elements are handpicked because they are expected to serve the research purpose. Sometimes the sample elements are selected because it is believed that they are representative of the population of interest. As long as the researcher is at the early stages of research, when ideas or insights are being sought—or when the researcher realizes its limitations—the judgment sample can be used productively. It becomes dangerous, however, when it is used in descriptive or causal studies and its weaknesses are overlooked.
Learning Objective 6
Define quota sample.
The quota sampling technique attempts to ensure that the sample is representative of the populationby selecting sample elements in such a way that the proportion of the sample elements possessing a certain characteristic is approximately the same as the proportion of the elements with the characteristic in the target population. This is accomplished by assigning each field-worker a quota that specifies the characteristics of the people the interviewer is to contact.
Learning Objective 7
Specify the two procedures that distinguish a stratified sample.
A stratified sample is a probability sample that is distinguished by the following two step procedure: (1) The parent population is divided into mutually exclusive and exhaustive subsets, and (2) a simple random sample of elements is chosen independently from each group or subset.
Learning Objective 8
Cite two reasons researchers might choose to use a stratified sample rather than a simple random sample.
Stratified samples can produce sample statistics that are more precise, meaning they have smaller error due to sampling than simple random samples. Stratification also allows the investigation of the characteristics of interest for particular subgroups.
Learning Objective 9
Note what points investigators should keep in mind when dividing a population into strata for a stratified sample.
Investigators should divide the population into strata so that the elements within any given stratum are as similar in value as possible, and so that the values between any two strata are as disparate as possible.
Learning Objective 10
Explain the difference between a proportionate stratified sample and a disproportionate stratified sample.
With a proportionate stratified sample, the number of observations in the total sample is allocated among the subgroups, or strata, in proportion to the relative number of elements in each stratum in the population. Disproportionate stratified sampling involves balancing the two criteria of strata size and variability. With a fixed sample size, strata exhibiting more variability are sampled more than proportionately to their relative size. Conversely, those subgroups that are very homogeneous are sampled less than proportionately.
Learning Objective 11
List the steps followed in drawing a cluster sample.
Cluster sampling involves the following steps: (1) The parent population is divided into mutually exclusive and exhaustive subsets, and (2) a random sample of the subsets is selected.