Math 225 Course Notes
Section 1.4: The Simple Random Sample
There are many ways of taking random samples,
the most theoretically important of which is the simple random sample.
In this book, all random samples are assumed to be simple.
Other important methods of random sampling in practice include
stratified random sampling and multi-stage sampling.
A simple random sample is a sample that is chosen according to
a procedure where all samples of the same size have the same chance of being
This is just like picking names from a hat.
Data from simple random samples are the easiest to analyze.
However, there are reasons for using other sampling methods.
To insure that there is sufficient representation from various groups,
a researcher could take a stratified random sample.
This is accomplished by taking a simple random sample
from each of several groups.
Another common sampling scheme is multi-stage sampling.
For example, to take a sample of households:
It is not necessary to have a complete national list of households,
and travel between households will be easier.
- Take a random sample of counties in the U.S.
- Then, take a random sample of townships within each county.
- Then, take a random sample of voting blocks within each township.
- Finally, take a random sample of households within each voting block.
We will only study data from simple random samples.
Last modified: Jan 15, 1996