GRADE 8 RESEARCH
QUARTER 3
Let’s Understand (Study the Concept)
SAMPLING
Sampling is the process of selecting a representative group
from the population under study (McLeod, 2019). A population is the
entire group that you want to draw conclusions about. In research, it
can mean a group of variables of elements of anything (objects,
events, species, organism, etc) you want to study. On the other hand,
a sample is the specific group that you will collect data from. The
size of the sample is always less than the total size of the population
(Scribbr, 2021).
When you collect data from a population or a sample, there
are various measurements and numbers you can calculate from the
data. A parameter is a measure that describes the whole population
while statistic is a measure that describes the sample.
Purpose of Sampling
The purpose of sampling is to provide various types of statistical information of a qualitative or quantitative
nature about the whole by examining a few selected units. The sampling method is the scientific procedure of selecting
those sampling units which would provide the required estimates with associated margins of uncertainty, arising from
examining only a part and not the whole.
However, sampling is limited or may not be feasible for problems that require very high accuracy and or errors
may occur if sampling is high
Sampling Methods (Types of Samples)
There are two categories of sampling – randomized (probability sampling) and non-randomized (nonprobability sampling). A randomized sample involves random selection, allowing you to make strong statistical
inferences about the whole group. A non-randomized sample involves non-random selection based on convenience
or other criteria, allowing you to easily collect data.
1)
2)
Randomized Sample/Probability sampling technique
a. Simple random sampling - randomly selected subset of a population. In this sampling method, each
member of the population has an exactly equal chance of being selected
b.
Systematic random sampling - similar to simple random sampling, but it is usually slightly easier to
conduct; Every member of the population is listed with a number, but instead of randomly generating
numbers, individuals are chosen at regular intervals
c.
Stratified sampling - involves dividing the population into subpopulations that may differ in important
ways; in this type of sample, it allows you draw more precise conclusions by ensuring that every subgroup
is properly represented in the sample
d.
Cluster sampling - also involves dividing the population into subgroups, but each subgroup should have
similar characteristics to the whole sample; instead of sampling individuals from each subgroup, you
randomly select entire subgroups
e.
Multi-stage sampling - a sampling method that divides the population into groups (or clusters) for
conducting research; complex form of cluster sampling; also known as multi-stage cluster sampling; in
this sample method, significant clusters of the selected people are split into sub-groups at various stages
to make it simpler for primary data collection; example: Gallup polls
Non-randomized/Non-probability sampling technique
a. Convenience sampling - includes the individuals who happen to be most accessible to the researcher
b. Purposive/judgment sampling - involves the researcher using their expertise to select a sample that is
most useful to the purposes of the research
c.
Snowball sampling - to recruit participants via other participants; the number of people you have access
to “snowballs” as you get in contact with more people
d.
Voluntary response sample - mainly based on ease of access; instead of the researcher choosing
participants and directly contacting them, people volunteer themselves (e.g. by responding to a public
online survey); voluntary response samples are always at least somewhat biased, as some people will
inherently be more likely to volunteer than others
e.
Quota sampling - researchers create a sample involving individuals that represent a population;
researchers choose these individuals according to specific traits or qualities; two types – controlled quota
and uncontrolled quota
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