Other Sampling Methods Lecture 8 Sections 2.6 – 2.7 Tue, Jan 29, 2008.
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Other Sampling Methods Lecture 8 Sections 2.6 – 2.7 Tue, Jan 29, 2008
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Transcript of Other Sampling Methods Lecture 8 Sections 2.6 – 2.7 Tue, Jan 29, 2008.
Other Sampling Methods
Lecture 8
Sections 2.6 – 2.7
Tue, Jan 29, 2008
Stratified Random Sampling Stratified random sample
Stratified Random Sampling Normally the members within each stratum
share a common characteristic that they do not share with members of the other strata.
That is, each stratum is homogeneous.Male vs. female.Resident vs. non-resident.
Stratified Random Sampling
The population
Stratified Random Sampling
The population
The strata
Stratified Random Sampling
The population
One stratum
Stratified Random Sampling
The population
One stratum
Anotherstratum
Stratified Random Sampling
The population
A simple random samplefrom this stratum
Stratified Random Sampling
The population
A simple randomsample fromthis stratum
A simple random samplefrom this stratum
Stratified Random Sampling
The population
Simple random samples from all strata
Stratified Random Sampling
The population
The stratified random sample
Example
Let the population consist of males Andy, Bob, Charlie, Don, Ed, Fred, Greg, and Hank and females Pam, Queeny, Rachel, Susie, Terri, Uzi, Valerie, and Wendy.
Choose a stratified sample of size n = 8, where the strata are the two sexes.
Is the sample representative with regard to sex?
Why Stratified Samples?
If we know the proportion of the population that each group comprises, then we increase our chances of getting a representative sample by using a stratified sample.
Strata vs. Populations
We may be genuinely interested in the differences among the strata.For example, pollsters studying elections
routinely categorize their samples by gender, and ethnic group, party affiliation, etc.
However, in that case, the strata are better viewed as distinct populations.
Cluster Sampling
Cluster Sampling
Cluster Sampling
Note that it is the clusters that are selected at random, not the individuals.
It is hoped that each cluster by itself is representative of the population, i.e., each cluster is heterogeneous.
Cluster Random Sampling
The population
Cluster Random Sampling
The population
The clusters
Cluster Random Sampling
The population
One cluster
Cluster Random Sampling
The population
One cluster
Anothercluster
Cluster Random Sampling
The population
A random sampleof clustersSelect all of these
And all of these
Cluster Random Sampling
The population
The cluster random sample
Example
Now suppose thatAndy, Bob, Pam, and Queeny live in
Fredericksburg.Charlie, Don, Rachel, and Susie live in
Richmond.Ed, Fred, Terri, and Uzi live in Charlottesville.Greg, Hank, Valerie, and Wendy live in
Roanoke.
Example
Use cluster sampling to choose a sample of size n = 8, where the clusters are the cities.
Is the sample representative with regard to sex?
Is the sample representative with regard to geographic location?
Stratified Sampling vs. Cluster Sampling In stratified sampling
From all of the strata we take randomly selected individuals.
In cluster samplingFrom randomly selected clusters we take all
of the individuals.
Stratified Sampling vs. Cluster Sampling It is done this way because In stratified sampling, the members of a
stratum have some characteristic in common (homogeneous).
In cluster sampling, the members of each cluster are believed to resemble the entire population (heterogeneous).
