September 26, 2011
The 6 Sample
Survey Methods
So far, we have discussed two BAD
methods…
1.
Voluntary Response Method
People who respond usually have strong
opinions, causing bias to occur.
You respond by write in, call in, or Internet
voting.
This method is easy to conduct, you get fast
results, and it’s usually more cost effective.
What are some examples you have
participated in?
2.
Convenience Sampling Method
The people surveyed are the easiest to reach
(same room, same store, etc.).
The people surveyed are biased because they
have this similarity to share. Even if they are
“randomly” chosen, anyone who does not use
that store, attend that class, etc., is
automatically excluded.
This method is also easy to conduct.
…and one GOOD method…
3.
Simple Random Sample (SRS)
 Every person has an equal chance of being
chosen to be a part of sample.
 Participants are chosen by a table of
random digits, a calculator or computer, or
just by drawing names from a hat.
 Bias could still occur because some groups
could be under represented as a result of
this random sampling (“under coverage”)
And now for some other types of
samples…
4.
Systematic Sample
Each member of the population is assigned a
number. The starting number is randomly
selected, and then the sample members are
selected at random intervals from the starting
member.
Example: randomly chose the 15th person,
then the interval was every 4th person after
that, so the 15th, 19th, 23rd, 27th, and so on,
were chosen for the survey.
Systematic Sample…
 Be
careful using this in case there are regularly
occurring patterns already in the population
(every 4th person has a common quality).
 A problem here is that as soon as the starting
number and interval are determined, the
randomness for the other numbers is gone and
everyone on the list knows if they will or will
not be chosen.
Cluster Sample…
5.
Cluster Sample
Can be used when the population falls into
naturally occurring subgroups (like zip codes).
To select a cluster sample, divide the
population into groups (clusters) and select all
the members in one or more (but not all) the
clusters.
Other examples: different periods of the
same course, different branches of a bank, etc.
Cluster Sample…
 Groups
which are not chosen are now
experiencing under coverage. They must
rely on the results from other groups,
hoping that they will effectively represent
their interests.
Stratified Random Sample…
6.
Stratified Random Sample
Divide the sampling frame (everyone
you are choosing from) into distinct
groups (strata).
Take SRS’s of each strata.
Example: If there is concern about
under coverage for ethnicity/race, this
could reduce/eliminate that by creating
strata for each identified group.
Stratified Random Sample…
 The
benefit here is that all groups are
represented.
 But will the groups get the same number
of participants or the same ratio of
participants???
 If every group is given an equal count,
under coverage can occur again. So they
must be given the same RATIO of
participants.
So, what do you think???
1.
 2.
 3.
 4.
 5.
 6.


Voluntary Response Sample
Convenience Sample
Simple Random Sample
Systematic Sample
Cluster Sample
Stratified Random Sample
Which are good, which are bad, which are
both?