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Sampling From Populations
Chapter 5 Sampling From Populations
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Why Do Researchers Select Samples?
In the behavioral sciences, a population is a group that a researcher is interested in answering a question about Researchers select samples mostly because they do not have access to all individuals in a population Ex. Suppose you want to get an idea of how people in general feel about a new pair of shoes you just bought Ask 20 people at random throughout the day You only asked 20 people (your sample) to get an idea of the opinions of people in general (the population of interest)
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Subjects, Participants, and Sampling Methods
Subjects and participants Participant: Used to describe a human who volunteers to be subjected to the procedures in a research study Subject: Used to describe a nonhuman that is subjected to procedures in a research study and to identify the names of research designs
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Subjects, Participants, and Sampling Methods
Selecting samples from populations When researchers identify a population of interest, the population they identify is typically very large Target population: All members of a group of interest to a researcher Ex. U.S. students choosing a college Accessible population (also called sampling frame): The portion of the target population that can be clearly identified and directly sampled from U.S. students at one or more local high schools choosing a college
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Subjects, Participants, and Sampling Methods
Representative sample: One in which the characteristics of individuals or items in the sample resemble those in a target population of interest Probability sampling: Category of sampling in which a sample is selected directly from the target population Nonprobability sampling: Category of sampling in which a sample is selected from the accessible population Commonly used to select samples in behavioral research
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Methods of Sampling: Nonprobability Sampling
Convenience sampling – Subjects or participants are selected based on how easy or convenient it is to reach or access them and based on their availability to participate Subject pool: Group of accessible and available participants for a research study (Ex. College students) Most common method of sampling in behavioral research Drawback is that it does not ensure that a sample will be representative
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Methods of Sampling: Nonprobability Sampling
Quota sampling – Subjects or participants are selected based on known or unknown criteria or characteristics in the target population Simple quota sampling: Used when little is known about the characteristics of the target population An equal number of subjects or participants are selected for a given characteristic or demographic Proportionate quota sampling: Used when the proportions of certain characteristics in a target population are known Subjects or participants are selected such that the known characteristic or demographics are proportionately represented in the sample
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Methods of Sampling: Nonprobability Sampling
Snowball sampling (aka chain-referral sampling)– technique where existing study subjects recruit future subjects from among their acquaintances Advantage: locates people of particular population otherwise difficult to find (homeless, illegal drug users) Participant crosstalk becomes a significant issue Community bias
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Methods of Sampling: Probability Sampling
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Methods of Sampling: Probability Sampling
Simple random sampling – All individuals in a population have an equal chance of being selected and are selected using sampling with replacement Sampling with replacement: Individual selected is replaced before the next selection to ensure that the probability of selecting an individual is always the same Sampling without replacement: when each individual selected is not replaced before the next selection, is most often used by behavioral researchers
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Methods of Sampling: Probability Sampling
Systematic sampling – The first participant is selected using simple random sampling, and then every nth person is systematically selected until all participants have been selected
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Methods of Sampling: Probability Sampling
Stratified random sampling – Population is divided into subgroups or strata; participants are then selected from each subgroup using simple random sampling, and combined into one overall sample
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Methods of Sampling: Probability Sampling
Cluster sampling – Subgroups or clusters of individuals are identified in a population, and then a portion of clusters that are representative of the population are selected such that all individuals in the selected clusters are included in the sample
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Stratified sample: wants low variance within strata, high variance between strata.
Cluster sample: wants high variance within clusters, low variance between clusters. Also assumes it's cheap to sample within a cluster, expensive to sample many clusters.
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Sampling Error and Standard Error of the Mean
Sampling error – Extent to which sample means selected from the same population differ from one another Indicates that characteristics in a sample can vary from those in the population Standard error of the mean – Standard deviation of a sampling distribution of sample means. It is the standard error or distance that sample mean values can deviate from the value of the population mean Numeric measure of sampling error One way to reduce standard error is to increase the size of the sample
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Potential Biases in Sampling
Sampling bias (or selection bias) – The sampling procedures employed favor certain individuals or groups over others It can lead to the selection of a sample that is not representative of the target population, but only the overrepresented groups in the sample May be problematic for research that uses online surveys The potential portion of population sampled favors participants with greater aptitude and experience with computers and those with access to more compatible computer systems
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Potential Biases in Sampling
Nonresponse bias – A number of participants in one or more groups choose not to respond to a survey or request to participate in a research study Individuals in a population who respond to surveys or postings asking for participants are likely to be systematically different from those who do not Results in a sample that is not representative
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