1. Other Sampling Methods
Lecture 8
Sections 2.6
Tue, Sep 4, 2007

2. Stratified Random Sampling
Stratified random sample

3. 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.

4. Stratified Random Sampling
The population

5. Stratified Random Sampling
The strata
The population

6. Stratified Random Sampling
One stratum
The population

7. Stratified Random Sampling
One stratum
Another
stratum
The population

8. Stratified Random Sampling
A simple random sample
from this stratum
The population

9. Stratified Random Sampling
A simple random sample
from this stratum
A simple random
sample from
this stratum
The population

10. Stratified Random Sampling
Simple random samples from all strata
The population

11. Stratified Random Sampling
The stratified random sample
The population

12. Example
Let the population be Andrea, Barry, Chantal, Dean, Erin, Felix, Gabrielle, and Humberto.
Choose a stratified sample of size n = 4, where the strata are the two sexes.
Is the sample representative with regard to sex?

13. 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.

14. 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.