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SamplingSampling
A A populationpopulation is all individuals of interest is all individuals of interest
to a researcherto a researcher
•• For identical twins research the population For identical twins research the population
would be all individuals with an identical twin.would be all individuals with an identical twin.
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A A samplesample is a subset of the population is a subset of the population
that is selected to participate in the that is selected to participate in the
research.research.
•• 200 identical twins randomly selected from the 200 identical twins randomly selected from the
population participated in the research.population participated in the research.
Confidence IntervalsConfidence Intervals
Data collected from the sample are used Data collected from the sample are used
to make inferences about the variables of to make inferences about the variables of
interest in the population.interest in the population.
Inferences can contain error (sampling Inferences can contain error (sampling
error) which is estimated and used to error) which is estimated and used to
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error) which is estimated and used to error) which is estimated and used to
provide a provide a confidence intervalconfidence interval
•• A confidence interval is a range of values A confidence interval is a range of values
drawn from the sample that the researcher is drawn from the sample that the researcher is
95% sure are true for the population.95% sure are true for the population.
A larger sample size (up to a point) A larger sample size (up to a point)
provides a more accurate prediction of the provides a more accurate prediction of the
true population value.true population value.
Unbiased SamplingUnbiased Sampling
To insure an accurate sample, researchers must:To insure an accurate sample, researchers must:
•• Randomly sample from a population that contains all Randomly sample from a population that contains all
members of that populationmembers of that population
•• Collect data fr om ALL participant s in the selected C ollect data from A LL participants in the selected
sample.sample.
Completely unbiased samples are rare and truly Completely unbiased samples are rare and truly
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Completely unbiased samples are rare and truly Completely unbiased samples are rare and truly
random samples are often difficult to obtain.random samples are often difficult to obtain.
•• Researchers tolerate nonrandom samples because they Researchers tolerate nonrandom samples because they
are not trying to estimate population values but are are not trying to estimate population values but are
investigating gene ral relationships bet ween variables invest igating general relat ionships between var iables
within a population.within a population.
Sampling TechniquesSampling Techniques
Probability SamplingProbability Sampling
•• Each member of the population has a Each member of the population has a
specifiable probability of bein g selectedspecifiable probability of being selected
Simple random sampling: each person has an equal Simple random sampling: each person has an equal
probability of being sele ctedprobability of being selected
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probability of being sele cted
.
probability of being sele cted
.
Stratified random sampling: the total population is Stratified random sampling: the total population is
divided into relevant “strata” (or subdivisions) and divided into relevant “strata” (or subdivisions) and
then members of each strata are randomly selectedthen members of each strata are randomly selected
Cluster sampling: the population is organized in Cluster sampling: the population is organized in
clusters and then a subset of clusters is randomly clusters and then a subset of clusters is randomly
selected, then all individuals within the cluster are selected, then all individuals within the cluste r are
sampled.sampled.
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