Types of Sampling
Voluntary Response Sample
Definition
A voluntary response sample consists of people who chose themselves by responding to a
general appeal. (Be Aware) They often over represent people with strong opinions, most often
negative opinions.
Example
For example, if there was pre-election coverage taking place on TV and the screen provided a
number a person could call to "vote" for or against a certain candidate being interviewed, the
people watching would be able to choose whether or not they wanted to take part in the survey,
and thus this would be a voluntary response sample.
Case Study
The advice columnist Ann Landers once asked her readers, "If you had it to do over again, would
you have children?" A few weeks later, her column was headlined "70% OF PARENTS SAY
KIDS NOT WORTH IT." Indeed 70% of the nearly 10,000 parents who wrote in said they
would not have children if they could make the choice again.
These data are worthless as indicators of opinion among all American parents. The people who
responded felt strongly enough to take the trouble to write Ann Landers. Their letters showed
that many of them were angry at their children. These people don't fairly represent all parents. It
is not surprising that a statistically designed opinion poll on the same issue a few months later
found that 91% of parents would have children again. Ann Landers announced a 70% "No"
result when the truth about parents was close to 90% "Yes."
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Types of Sampling
Simple Random Sample
Definition
Simple random sampling is the basic sampling technique where we select a group of subjects (a
sample) for study from a larger group (a population). Each individual is chosen entirely by
chance and each member of the population has an equal chance of being included in the sample.
Every possible sample of a given size has the same chance of selection; that is, each member of
the population is equally likely to be chosen at any stage in the sampling process.
Example
Let's assume that we are doing some research with a small service agency that wishes to asses
client's views of quality of service over the past year. Decide on the number of clients you would
like to have in the final sample. For the sake of the example, let's say you want to select 100
clients to survey and that there were 1000 clients over the past 12 months. Then, the sampling
fraction is f = n/N = 100/1000 = .10 or 10%. Now, to actually draw the sample, you have several
options. You could print off the list of 1000 clients, tear then into separate strips, put the strips in
a hat, mix them up real good, close your eyes and pull out the first 100. But this mechanical
procedure would be tedious and the quality of the sample would depend on how thoroughly you
mixed them up and how randomly you reached in. Perhaps a better procedure would be to use
the kind of ball machine that is popular with many of the state lotteries. You would need three
sets of balls numbered 0 to 9, one set for each of the digits from 000 to 999 (if we select 000
we'll call that 1000). Number the list of names from 1 to 1000 and then use the ball machine to
select the three digits that selects each person. The obvious disadvantage here is that you need to
get the ball machines.
Case Study
The latest New York Times/CBS New Poll is based on telephone interviews conducted May 29
through June 2 with 1,509 adults around the United States, excluding Alaska and Hawaii.
The sample of telephone exchanges called was selected by a computer from complete list of
exchanges in the country. The exchanges were chosen to sure that each region of the country was
represented in proportion to its population. For each exchange, the telephone numbers were
formed by random digits, thus permitting access to both listed and unlisted residential
numbersThe results have been weighted to take account of household size, and to adjust for
variations in the sample relating to region, race, sex, age and education.
In theory, in 19 cases out of 20 the results based on such sample will differ by not more than 3
percentage points in either direction from what would have been obtained by interviewing all
adult Americans. The error for smaller subgroups is larger. For example, the margin of sampling
error for Democrats or Republicans is plus or minus 4 percentage points.In addition to sampling
error, the practical difficulties of conducting any survey of public opinions may introduce other
source of error into the poll.
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Types of Sampling
Stratified Random Sample
Definition
To choose a stratified random sample, divide the population into strata, groups of individuals
that are similar in some way that is important to the response. Then choose a separate SRS from
each stratum and combine these SRSs to form the full sample.
Example
A school official wants to estimate the average number of hours per week that students devote to
homework. Because she believes that this figure will differ considerably among classes, stratified
random sample will be employed. The population of students at this school will be group into
four strata consisting of all freshman, sophomore, juniors and seniors. From each stratum, a
random sample of students will then be selected. The resulting information can be combined to
obtain an estimate that is expected to be more precise than that obtained from a random sample
of the entire population.
Convenience Sample
Definition
A convenience sample chooses the individuals that are easiest to reach or sampling that is done
easy. Convenience sampling does not represent the entire population so it is considered bias.
Example
Interviewing people at a shopping mall as they walk by. This is easy because you just choose it,
without any random mechanism. You just choose the people that walk by you as your standing
there. Sometimes the people could ignore you so it all depends what your surveying.
OR
Or if you want to choose 5 people from a class of 50. You could choose : First 5 students who
raise their hand. First 5 students in the first row. 5 tallest students .
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Types of Sampling
Systematic Sample
Definition
In a systematic sample every kth item is included in the sample.
Example
Suppose we want to know what seniors plan to do after graduation. All seniors at North High
School take English 4. Let's say there are 12 such classes and we want to distribute the survey to
3 classes. We randomly assign each class a number between 1 and 12. Since we want to choose 3
classes we randomly pick a number between 12/3 = 4 and 1. Suppose the number 2 comes up.
Then we choose the classes with the following numbers: 2, 2+4 = 6, and 2 + 8 = 10.
Cluster Sample
Definition
Cluster sampling is a sampling technique where the entire population is divided into groups, or
clusters, and a random sample of these clusters are selected. All observations in the selected
clusters are included in the sample.
Example
Suppose that the Department of Agriculture wishes to investigate the use of pesticides by farmers
in England. A cluster sample could be taken by identifying the different counties in England as
clusters. A sample of these counties (clusters) would then be chosen at random, so all farmers in
those counties selected would be included in the sample. It can be seen here then that it is easier
to visit several farmers in the same county than it is to travel to each farm in a random sample to
observe the use of pesticides.
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