Systematic random sampling is a probability sampling technique that ensures each unit in a population has an equal chance of selection. The document illustrates this with an example of selecting 100 students from a population of 10,000 at Radin Global University, detailing the steps involved in the process. It emphasizes the importance of a structured approach to achieve a representative sample for research.

1. by: Jose Radin L. Garduque

2. Systematic Random
Sampling is a type
of probability
sampling
technique where
there is an equal
chance of
selecting each
unit from within
the population
when creating the
sample.

3. Let us have an
example of using
this random
sampling. Imagine
that a researcher
wants to
understand more
about the career
goals of students
at Radin Global
University…

4. Let’s say the
university has
10,000 students.
These students
are our
population (N). In
order to select a
sample (n) from
those students,
we need to follow
the seven steps of
SRS!

5. In our example,
the population
is 10,000
students at
Radin Global
University. The
said population
is expressed as
“N”.

6. Let’s imagine
that we choose
a sample size
of 100
students. The
sample is
expressed as
“n”.

7. To select a
sample of 100
students, we
need to identify
all 10,000
students by
asking for a
student list
from the Office
of the
Registrar.

8. Assign a
consecutive
number from 1
to N, next to
each student.
In our case,
this would
mean 1 to
10,000.

9. Assuming that
we have chosen
the sample size
of 100
students, we
have to divide
n/N, so that 1
student is
selected in
every 100

10. Imagine the 1st
unit was
number 9,
since this
number fits
between 0 and
100. As such,
our first
student would
be the 9th
on
our list of

11. We now select
the remaining
99 students by
using the 9th
student as the
starting point
until it goes to
the 109th
, 209th
,
309th
and so
forth.

12. A Report in Educ.
404
(Statistics for
Educational
Research)
under Dr. Felimon
Pimentel in Filamer
Christian
University,
Roxas City,
Philippines