1
See Systematic Random Sampling at Wikipedia
2
Refer to ‘What Are the Advantages and Disadvantages of Systematic Random Sampling’,

sampling.asp
SYSTEMATIC RANDOM SAMPLING
4
COMPARISON BETWEEN SIMPLE, SYSTEMATIC, AND STRATIFIED SAMPLING METHOD
Type of Sampling Methods
Description
Advantages
Disadvantages
Simple Random Sampling
•
Sample drawn using
random number
table/generator.
•
Produces defensible
estimates of the
population and sampling
error.
•
Simple sample design and
interpretation.
•
Costlier  requires a
complete list of all
potential respondents to
be available beforehand.
•
High chance of having a
biased representation of
the population.
•
Time consuming for large
population.
Systematic Random
Sampling
•
Selects an element of the
population at a random
starting point and a fixed,
periodic interval.
•
The sampling interval, is
calculated by dividing the
population size by the
desired sample size.
•
Simple.  Researchers
have a degree of control.
•
Ensures cases are spread
across the population.
•
Can be costly and time
consuming due to
obtaining the population
list.
•
Likely to choose common
sample if there is
periodicity in the
population list.
Stratified Random
Sampling
•
Divided into
subpopulations or strata
based on shared attributes
and uses simple random
on each stratum.
•
Results may be weighted
or combined.
•
Ensures units from each
main group are included
and may therefore be
more reliably
representative.
•
Should reduce the error
due to sampling.
•
Selecting the sample is
more complex and
requires good population
information.
•
The estimates involve
complex calculations.
SYSTEMATIC RANDOM SAMPLING
5
HOW DOES ONE CONDUCT A SYSTEMATIC RANDOM SAMPLING?
3
To construct a systematic random sampling, one must: 
1.
Firstly, define the population, meaning they must decide on what they want to study
and the target group. Thus, they also need to establish their sampling frame,
consisting of their target group of people in an ordered fashion.
2.
Secondly, they should determine the sample size. This can be done by using the
sample size calculation. Margin of error, population size, and confidence level is
needed to calculate the sample size.
3.
A list of the elements of the population is needed. This makes it easier when we want
to assign numbers to population list.
4.
Next, is to assign numbers to the population list. This step is to make determining the
sample easier.
5.
In order to choose the sample, a
k
th figure is needed. To calculate
k
, the population,
N, is divided by the sample size, n.
k
= N/n
e.g:
k
= 1000/100 =10 (every
10
th person is chosen)
6.
Next, we have to select the first unit by generating the random number, range from
1N, using a software or application online.
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 Summer '17
 Putri