Methodology Chapter 1 sampling - Copy.pptx

Sampling and it’s
Techniques

Population, Sample and Sampling
 The population refers to the totality
of objects, elements, person and
characteristics under a given
condition. In other words,
population refers to the entire group
that you want to draw conclusions
about

 On the other hand, sample is the
specific group that you will collect
data from which also refers as the
subset in a population. Sampling in
contrary is the process of technique
of choosing a sample from a
population to participate in the
study.

 In research, the people or things
being studied are called subjects or
respondents.
 • Subjects are the main focus of
the study.
 • Respondents are the people
who give information during data
collection.
 • Sometimes, subjects and
respondents are the same, but not
always. Subjects can also be groups
or things

 Subjects vs. Respondents
 • Example 1: A study about the
favorite food of Grade 11 students.
 o Subjects: Grade 11 students
(because they are the focus of the
study).
 o Respondents: The students
who answer the survey (because
they provide information).

 • Example 2: A study about the
cleanliness of different classrooms.
 o Subjects: The classrooms
(because they are being studied).
 o Respondents: The students
and teachers interviewed about
cleanliness.

Types and Subtypes of Sampling
 Probability sampling is a type of sampling in
which all the members of an entire population
have a chance of being selected. This is also
called scientific sampling.
 Non-probability sampling means that not every
individual in the population has an equal
chance of being selected.
 Instead, participants are chosen based on
specific characteristics, availability, or
recommendations.

PROBABILTY
SAMPLING
TECHNIQUES

• Simple random sampling
 • is a method of choosing samples in which
all the members of the population are given an
equal chance of being selected. There are
various ways of obtaining samples through
simple random sampling (Treece & Treece,
1986). These include the roulette wheel,
fishbowl method, and the use of a table of
random numbers.

 1. Roulette Wheel Method
 🔹 Definition:
 • A roulette wheel selection is a
probability-based selection method where
participants or items are chosen based on
assigned probabilities.
 Example
 In a research study, students are assigned
different probabilities of being chosen based on
attendance. A computer or researcher "spins"
the roulette wheel, and a student is selected
randomly but with weighted chances.

 2. Fishbowl Method (Lottery Method)
 🔹 Definition:
 • The Fishbowl Method (also called the
Lottery Method) is a simple random sampling
technique where participants/items are drawn
randomly from a container, similar to picking
raffle tickets from a fishbowl.
 🔹 Example:
 • A teacher writes the names of all
students in a class, places them in a bowl, and
randomly selects five students for a special
task.

Stratified Random Sampling
 is a probability sampling method where a
population is divided into subgroups (strata)
based on shared characteristics, and then
participants are randomly selected from each
stratum.
 Example 1: Survey on Study Habits
 • Population: All Grade 12 SHS students.
 • Strata: Academic tracks (STEM, HUMSS,
ABM, TVL).
 • Sampling: Randomly pick proportional
students from each track (e.g., if STEM has
more students, select more from STEM).

• Cluster sampling
 • is used in large-scale studies, where the
population is geographically spread out.
Sampling procedures may be difficult and time-
consuming. For example:
 • A national education survey might divide
the country into regions (clusters) and
randomly select only a few regions instead of
sampling individuals from every part of the
country.
 • A study on student performance might
divide students by schools (clusters) and
survey all students in a few selected schools
instead of picking students from each school.

NONPROBABILTY
SAMPLING
TECHNIQUES

• Convenience sampling.
 It is also called accidental or incidental
sampling. No strict selection criteria; based on
convenience rather than randomness.
 Examples:
 • A college professor surveys students from
his own class instead of the whole school.
 • A researcher interviews shoppers at a
nearby mall instead of going city-wide.

Quota sampling
 • is somewhat similar to stratified
sampling, in that the population is divided into
strata, and the researcher deliberately sets
specific proportions in the sample, whether or
not the resulting proportion is reflective of the
total population. This is commonly done to
ensure the inclusion of a particular segment of
the population.
 Example:
 • A survey requires 100 respondents: 50
men and 50 women, so researchers choose
people until the quota is filled.

Purposive sampling
 • involves handpicking subjects, usually to
suit very specific intentions. This is also called
judgmental sampling.
 Example:
 • A research project on elite athletes'
mental health only selects Olympic athletes.

Snowball Sampling
 • is a non-probability sampling method
where researchers recruit participants through
referrals from existing participants. It is often
used when the population is hard to reach or
hidden (e.g., marginalized groups, secretive
communities
 Example:
 • Study on Drug Users Researchers find
→
one participant, who refers more users.
 • Research on LGBTQ+ Experiences A
→
participant introduces their friends who fit the
study criteria.

Theoretical Sampling
 • is a qualitative sampling method used in
Grounded Theory Research, where data
collection is guided by emerging findings.
Instead of selecting all participants at once,
researchers adjust the sample as the study
progresses based on what they learn.
 Example:
 • Study on Student Motivation If early
→
findings show that family influence is
important, the researcher seeks more
participants who can expand on that idea (e.g.,
parents, teachers).

Instruction: Answer the following
questions based on your
understanding in this lesson. Make
your answers brief yet substantial.
 1. What is the difference between population and
sample?
 2. What do you think is the main reason why
researchers prefer to use purposive sampling in
the conduct of their research?

DIRECTION: Direction: Complete the
table below by supplying the needed
information in each item. Make your
answers brief but substantial. Answer
in a separate sheet

Direction: Evaluate the following
research topics and determine the
best sampling procedure to be
used. Add a brief explanation.
1. A study on the mental health
challenges of doctors working in
emergency rooms..
Sampling Procedure:
______________________________
_____________________________
Explanation:

2. Research on the social media habits of
senior high school students in
different academic tracks (STEM,
HUMSS, ABM, TVL)..
Sampling Procedure:
______________________________
______________________
Explanation:

3. A study on traditional wedding
practices among indigenous
communities, where researchers start
with one key informant and ask them
to refer other participants.:
Sampling Procedure:
Explanation:

4. A study on the impact of study
environments on student
concentration, where the researcher
only surveys students who are
present in the school library at the
time of data collection.
Sampling Procedure:
Explanation:

Errors of nonobservation
 Nonresponse is probably the most serious
of these errors.
 Arises in three ways:
 Inability of the person responding to
come up with the answer
 Refusal to answer
 Inability to contact the sampled
elements

Errors of observation
 These errors can be classified as
due to the interviewer, respondent,
instrument, or method of data
collection.

Methodology Chapter 1 sampling - Copy.pptx

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Methodology Chapter 1 sampling - Copy.pptx