2. There are different techniques on how sample of a
given population is determined. These could be:
1. Random Sampling Technique (Probability
Sampling Technique)
2. Non-Random Sampling Technique (Non-
Probability Sampling Technique)
SAMPLING TECHNIQUES
3. Random Sampling is the most commonly used sampling
technique in which each member in the population is given
an equal chance of being selected in the sample. It is usually
called fair sampling.
Non-random Sampling is a method of collecting a small
portion of the population by which not all the members in the
population are given the chance to be included in the
sample. It is usually called as a bias sampling.
4. Random Sampling
– The population refers to the whole group under study or
investigation. In research, the population does not always refer to
people. It may mean a group containing elements of anything you
want to study, such as objects, events, organizations, countries,
species, organisms, etc.
– A sample is a subset taken from a population, either by random
sampling or by non-random sampling. A sample is a
representation of the population where it is hoped that valid
conclusions will be drawn from the population.
5. Random Sampling
– Random sampling is a selection of n elements
derived from the N population, which is the subject
of an investigation or experiment, where each point
of the sample has an equal chance of being
selected using the appropriate sampling technique.
6. Types of Random Sampling Techniques
– Lottery sampling is a sampling technique in which each
member of the population has an equal chance of being
selected. An instance of this is when members of the
population have their names represented by small pieces of
paper that are then randomly mixed together and picked
out. In the sample, the members selected will be included.
7. Types of Random Sampling Techniques
– Systematic sampling is a sampling technique in which members
of the population are listed and samples are selected at intervals
called sample intervals. In this technique, every nth item in the
list will be selected from a randomly selected starting point.
k = N/n where: N = population size; and n = sample size
– For example, if we want to draw a 2000 sample from a population
of 6,000, we can select every 3rd person in the list. In practice, the
numbers between 1 and 30 will be chosen randomly to act as the
starting point.
8. Types of Random Sampling Techniques
– Stratified random sampling is a sampling procedure in which
members of the population are grouped on the basis of their
homogeneity. This technique is used when there are a number of
distinct subgroups in the population within which full representation is
required. The sample is constructed by classifying the population into
subpopulations or strata on the basis of certain characteristics of the
population, such as age, gender or socio-economic status. The
selection of elements is then done separately from within each stratum,
usually by random or systematic sampling methods.
9. Using stratified random sampling, select a sample of 400
students from the population which are grouped according to
the cities they come from. The table shows the number of
students per city.
City Population (N)
A 12,000
B 10,000
C 4,000
D 2,000
10. City Population (N) Sample (n)
A 12,000
B 10,000
C 4,000
D 2,000
To determine the number of students to be taken as sample from each
city, we divide the number of students per city by total population (N=
28,000) multiply the result by the total sample size (n= 400).
11. Types of Random Sampling Techniques
– Cluster sampling is sometimes referred to as area
sampling and applied on a geographical basis. Generally,
first sampling is performed at higher levels before going
down to lower levels. For example, samples are taken
randomly from the provinces first, followed by cities,
municipalities or barangays, and then from households.
12. NON-PROBABILITY SAMPLING
– Convenience sampling wherein the researcher
gathers data from nearby sources of information
exerting minimal effort. Convenience is being used
by persons giving questionnaires on the streets to
ask the passers-by.
13. NON-PROBABILITY SAMPLING
– Purposive sampling is also not considered a random
sampling since the respondents are being selected based
on the goal of the studies of the researcher. If the study is
about the students who are children of OFW, the
researcher will get samples who are children of OFW.
This excludes other students from being a sample.
15. Find the sample size of a population of 500 with 5%
margin of error.
𝒏=
𝟓𝟎𝟎
𝟏 +𝟓𝟎𝟎 (𝟎 . 𝟎𝟓
𝟐
)
𝒏=
𝟓𝟎𝟎
𝟏 + 𝟏 . 𝟐𝟓
𝒏=
𝟓𝟎𝟎
𝟐 .𝟐𝟓
=𝟐𝟐𝟐 . 𝟐𝟐=𝟐𝟐𝟑
“The larger the size of
the sample, the more
certain we can be sure
that the sample mean
will be good estimate
of the population
mean.”
16. Parameter & Statistic
– A parameter is a descriptive population measure. It is
a measure of the characteristics of the entire
population (a mass of all the units under
consideration that share common characteristics)
based on all the elements within that population.
17. Parameter & Statistic
Example:
1. All people living in one city, all-male teenagers
worldwide, all elements in a shopping cart, and all
students in a classroom.
2. The researcher interviewed all the students of a
school for their favorite apparel brand.
18. Parameter & Statistic
–Statistic is the number that describes the
sample. It can be calculated and observed
directly. The statistic is a characteristic of a
population or sample group.
19. Parameter & Statistic
Example:
1. Fifty percent of people living in the U.S. agree with the
latest health care proposal. Researchers can’t ask hundreds of
millions of people if they agree, so they take samples or part of
the population and calculate the rest.
2. Researcher interviewed the 70% of covid-19 survivors.
21. Identify the random sampling technique used in each
item.
1.You are given a list of all graduating students in your
school. You decide to survey every 10th student on the
list and ask them the organization that they belong.
2.You wish to make a comparison of the gender
differences in Mathematics performance. You divide the
population into two groups, male and female, and
randomly pick respondents from each of the group.
3.You write the names of each student in pieces of paper,
shuffles, and then draw eight names to answer a survey
on their ethical media practices.
22. 4. The organizer created a list of all
players, decided to survey every sixth
name on the list, and later asked those
players that were selected.
5. All players will be grouped according to
their age and will randomly choose players
from each group to measure their height.
23. Answer the following.
1. Using the Slovin’s formula, find the sample
size of a population of 2,000 with 10%
margin of error.
2. In systematic sampling, what every kth
element will be included in the sample of 200
from a population of 1,000.
