CRIM 430

Sampling

SamplingSampling is the process of selecting part of a populationTarget population represents everyone or everything that you are interested in studyingResearch Goals for Sampling

1. Select a sample that represents the larger population

2. Generalize from a sample to an unobserved population the sample is intended to represent

A sample is representative if the aggregate characteristics of the sample closely approximate those same aggregate characteristics in the population

Probability SamplingTo meet the goals of sampling, it is best to use probability samplingProbability sampling is a method of sampling in which each member of a population has a known chance or probability of being selectedSamples that are representative of the larger population share, in equal (or near equal) amounts, the variations found in the populationProbability sampling helps researchers achieve a representative sampleIt protects sampling from sampling bias and allows researchers the ability to estimate the sample’s representativeness

Sampling BiasSampling bias refers to selecting subjects in a way that will not result in a sample that is not representative of the populationExamples: Selecting the first 100 males encountered in a mall to

represent all males Interviewing judges that have viewpoints consistent

with a research question and not interviewing judges with inconsistent viewpoints

Unless a researcher uses probability sampling from the population, it is impossible to declare that your sample is representative of that population

Prob. Sampling Terminology

Population: Grouping of study elementsPopulation Parameter: Summary description of a given variable in a populationSampling Frame: List of potential study subjects that comprise the populationSample Element: The unit about which information is collected and that provides the basis of of analysisSample Statistic: Summary description of a given variable in the sampleIf a sample is representative of the population, the sample statistic should equal the population parameter for any given variable/characteristic

Application of TerminologyPopulation Women offenders aged 18-25

with children in CA criminal justice system (N=10,000)

Population Parameters

Average Age=22.7Average # of Children 2.5

Sampling Frame A list of all female offenders that meet the criteria

Sampling Element Female offenders chosen as part of the sample

Sample Statistics Average Age of Sample Selected=23.4Average Number of Children=3.1

Probability Sampling Designs

Simple Random Sampling=Selection is completed by applying a random number procedure (similar to flipping a coin) until the desired sample size is achievedSystematic Sampling=Every nth element in the list is selected. The “n” is calculated by dividing the total number in the population by the number desired in the sample (e.g., 100/1000)Stratified Sampling=Selection begins by organizing sampling frame by specific characteristics (e.g., gender) and then applying simple random or systematic sampling to select subjects

Probability Designs, Cont’d.

Disproportionate Stratified Sampling=Selection of a number disproportionate to their representation in the population in order to yield sufficient cases of “rare” casesMulti-Cluster Sampling=Selection begins by creating groups of elements followed by the selection of sampling elements from within each group or cluster

Non-Probability SamplingProbability sampling designs are not possible in many situationsNon-probability sampling is an alternative; however, the samples are not representative of the population from which they are drawnNon-probability sampling designs are prone to selection biasNon-Probability sampling designs are, therefore, weaker than probability sampling designs

Non-Probability Sampling Designs

Purposive or Judgmental Sampling: Identifying a sample based on the presence of a particular characteristicQuota Sampling: Identifying a sample using a matrix to represent the characteristics of the populationConvenience Sampling: Sample is selected because access is easy and convenientSnowball Sampling: Using one respondent to provide contact to 2-3 additional respondents—continuous process to identify a larger sample