Sampling Techniques

1. Sampling Techniques

2. Samples
• Having clearly identified a thesis
statement or question, as well as the
population, variables and type of data
involved, a researcher can begin to
conduct his or her study;
• To conduct research, data from a sample
must be collected, which could involve
medical testing, laboratory analyses,
surveys, etc.

3. Samples - Continued
• The sample must be:
1. representative of the population;
2. appropriately sized (the larger the
better);
3. unbiased;
4. random (selections occur by chance);
• The above criteria are interrelated.

4. Samples - Continued
• To ensure that the four criteria are
met, careful planning is needed (any
errors in the sample will result in
unreliable conclusions);
• One of several methods can be
chosen to achieve randomness when
selecting a sample.

5. Random Sampling
Methods
Six methods are commonly employed.
1. Simple Random Sampling
→ all individuals in the population have an
equal likelihood of being chosen;
→ for example, number all students and
select the numbers from a hat (minimize
the level of control that the researcher
has).

6. Random Sampling
Methods - Continued
2. Systematic Random Sampling
→ used when you are sampling a fixed percentage
of the population;
→ randomly select a starting point, then select
every nth individual;
→ n is referred to as the sampling interval
(n = pop size/sample size);
→ for example, number all students in a list,
randomly select a starting point in the list, and
select every nth individual.

7. Random Sampling
Methods - Continued
3. Stratified Random Sampling
→ population is divided into strata, or
groups;
→ randomly select members of each
stratum (the number selected is
proportional to the stratum’s size);
→ for example, divide our population into
9’s, 10’s, 11’s and 12’s, and randomly
select members in each grade.

8. Random Sampling
Methods - Continued
4. Cluster Random Sampling
→ population is organized into groups;
→ groups are randomly selected, and all
members of the group are sampled;
→ for example, divide our school into
homerooms, randomly select homerooms,
and sample all students in selected
homerooms.

9. Random Sampling
Methods - Continued
5. Multi-Stage Random Sampling
→ population is organized into groups;
→ randomly select groups, and then randomly
select members in these groups (an equal
number selected per group);
→ for example, repeat the steps for Cluster
Random Sampling, but then randomly select
students in each selected homeroom.

10. Random Sampling
Methods - Continued
6. Destructive Sampling
→ applicable to products only;
→ products chosen randomly,
tested for quality control.

11. Random Sampling
Methods - Continued
• The sampling method chosen depends
on the population of interest;
• Sometimes, methods can be
combined;
• Careful planning is the key to
generating reliable results – always
have contingency plans!

12. 1. Determine the type of
sampling method used in each
scenario.
a) The Ontario government randomly selects
five high schools in Ontario and surveys
each teacher in those schools.
Cluster random sampling

13. b) You wish to survey 100 employees at
Trillium Shopping Plaza (contains 216
stores). You randomly select 10
stores, then randomly select 10
employees from each store.
Multi-staged Random Sample

14. c) Every fiftieth family in the
Unionville telephone book is surveyed
by phone.
Systematic Random
Sample

15. d) Jonathon randomly selects three
cards from a standard deck of cards.
Simple Random Sample

16. 2. In a town of 120 000 people, smoking has
been banned in all restaurants. A
committee of students wants to find out
what the whole town thinks of this new
law. The committee wants to survey 1460
people. Which sampling technique is most
appropriate?