Week 6 Flashcards
Refers to the strategies used to select a given number of individuals or things from a population
Sampling
All the individuals or things the researcher is interested in for the study being undertaken
Population
A population that the researcher can potentially access
Accessible population
What is being compared in the study
Unit of analysis
A list of all those in the accessible pop, which is used to select those who will be included in the sample
Sampling frame
Helps to determine the probability that any individual in the sampling frame can be selected
Probability sampling
A sample that closely matches the population from which it was drawn
Representative sample
With this type of sampling, it is unknown what the chance was that an individual was selected
Non-probability sampling
Also referred to as simple random sampling, uses a procedure that seeks to select participants randomly from the population or sampling frame. When SRS is used, each member of the sampling frame has an equal probability of being selected.
Random sampling
Using this method, a researcher assigns a number to everyone who is on the list compiled from the sampling frame and put this number on a piece of paper and then put the paper in a hat. The researcher then selects a predetermined number of pieces of paper out of the hat individually. The number selected correspond to the names of those who will be included in the sample.
Lottery
Involves, for example, selecting a number from a hat, including the participant associated with the number in the sample, and then putting the number back in the hat so that it can be selected again
Sampling with replacement
Involves, for example, selecting a number from a hat, including the participant associated with the number in the sample, and not putting the number back into the hat
Sampling without replacement
Involves the researcher selecting the first person to be in the sample based on a random starting point and then selecting the remainder of the sample based on a fixed sampling interval
Systematic random sampling
Calculated by dividing the entire population by the desired sample size
Sampling interval
Use when a researcher is interested in comparing two or more subgroups (or strata) of the population
Stratified random sampling
Employed when the researcher wants the sample size of each group to be proportional and its representation to the population
Proportional stratified sampling
Employed when the researcher wants the sample size of each sub group to be disproportional in its representation to the population
Disproportional stratified sampling
Also known as area sampling and involves selecting a cluster of participants from the population
Cluster sampling
In which the sample is obtained by selecting the cluster
One-stage cluster
Involves selecting clusters at the first stage, and then selecting who will be in the sample from every selected cluster (second stage)
Two-stage cluster
Also referred to as accidental or availability sampling, involves selecting persons from the target population because they are accessible to the researcher
Convenience sampling
Involves selecting persons from the target population because of their fit with the purpose of the study and inclusion criteria
Purposive sampling
Involves selecting participants based on a criterion established by the researcher
Criterion sampling
First involves selecting participants from the target population because of their fit with the purpose of the study and inclusion criteria. Once the researcher finishes, surveying or interviewing the participant, he or she will ask the participant to tell others about the study. If someone the participants spoke with is interested in participating in the study, here she is instructed to call the researcher. In conversation with the researcher, she will determine if the person is eligible to participate in the study.
Snowball sampling
Involves obtaining a sample that is as representative as possible, in relation to potentially confounding variables and of a specific size
Quota sampling
Unusually demographic variables that are related to both the independent and dependent variable, causing a spurious association
Confounding variables
An association where the researcher thought there was a relationship between the independent and dependent variable; however, another variable explains away this relationship
Spurious association
In this type of sampling, the researcher wants the sample size of each subgroup of the confounding variable to be proportional in its representation to the population
Proportional quota sampling
In this type of sampling, the researcher wants the sample size of each subgroup to be disproportional in its representation to the public
Nonproportional quota sampling
A quota in which the researcher considers the quota separately
Noninterlocking quota
A quota in which the researcher considers the quota jointly
Interlocking quota
Produced by using sampling strategies that overrepresent a portion of the study population
Sampling error
Due to the difference between those who respond to the survey/questionnaire and those who did not and how the survey/questionnaire was administered
Nonsampling error
Due to the methods used to select the sample
Sampling bias
Allows researchers to determine the sample size required to produce a given effect size
Power analysis
Way of quantify the size of difference between two groups
Effect size
