SENIOR HIGH SCHOOL
12
Practical
Research 2
Quarter 2 – Lesson 1 – Activity Sheet 1
Sampling Procedure
WHAT I NEED TO KNOW
Competencies:
 The learner describes sampling procedure and sample (CS_RS12-Ilac-2)
Learning Objectives: At the end of the lesson, the learners shall be able to:
1. Describe sampling procedure and sample;
2. use Slovin’s Formula in determining the sample size; and
3. compare and contrast Probability and Non-Probability Sampling.
INTRODUCTION
After choosing the appropriate quantitative research design through
your thorough review of related studies, you may now determine the
sample size as well as the apt sampling procedure for your research.
Determining the appropriate sampling technique and the sample size is a
requisite in crafting your research methodology.
Sampling is the process of securing some of the elements of a
population. Determining the correct sample size and how the samples are
selected are necessary in ensuring the accuracy and precision of an
estimate leading to valid research findings. An element is a member of a
population who can provide information for the population. A population
consists of the total elements about which you can make inferences based
on the data gathered from a determined sample size
WHAT IS IT
Sample Size Determination
A sample (n) is a selection of respondents for a research study to
represent the total population (N). Making a decision about sample size
for a survey is important. Too large a sample may mean a waste of
resources, both human and financial. On the other hand, too small a
sample decreases the utilization of the results.
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
The following are some reasons for the use of samples:
1. A sample saves time compared to doing a complete census which
requires more time.
2. A sample saves money because it is less costly than conducting a
complete census.
3. A sample allows more particular attention to be given to a number of
elements than when doing a census.
4. There is a greater error in reporting results of a census caused by
inexperienced interviewers. There is less sampling error in a survey.
5. Some research studies in the industry may only be performed on a
sample of items. For example, testing the length of time a battery will last.
Slovin’s Formula in determining the Sample Size
The following information is needed to be able to determine the sample size
using Slovin’s formula.
 Population (N) consists of members of a group that a researcher is
interested in studying the members of a group that usually have
common or similar characteristics.
 Margin of error is the allowable error margin in research. A confidence
interval of 95% gives a margin of error of 5%; a 98% gives a margin of
error of 2%; a 99% confidence interval gives 1% margin of error.
The sample size can be obtained by the formula:
𝑛=
𝑁
1 + 𝑁𝑒 2
Where
n=sample size
N=total population
E=margin of error
Example 1:
A researcher wants to conduct a survey. If the population of a big
university is 35,000, find the sample size if the margin of error is 5%.
Substitute the given data,
𝑛=
35, 000
1 + (35, 000)(.05)2
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
𝑛=
35, 000
1 + (35, 000)(.0025)
𝑛=
35, 000
1 + 87.5
𝑛=
35, 000
88.5
𝑛 = 395
Note: Please see the attached sheet for the examples.
Sampling Procedures
Sampling is a formal process of choosing the correct subgroup called a
sample from a population to participate in a research study. The subgroup
shall be the representative of the large group from where they were
selected. To create a sample, you may follow any of the following
categories of sampling techniques: probability sampling and nonprobability sampling schemes.
1. Probability Sampling Procedures
The most important characteristic of probability sampling procedure is the
random selection of the samples. Specifically, each sample (n) or element
from the population (N) has an equal chance of selection under a given
sampling technique.
Types of Probability Sampling Procedures
 Simple Random Sampling - This is the most frequently used type of
probability sampling technique. This is characterized by the idea that the
chance selection is the same for every member of the population.
For example, assume that you want to conduct a survey of 100 senior
high school students in a certain private school. To get the desired
sample size of 100, you can do the selection process , either manually
or electronically, ensuring that each student in the population has an
equal chance of being drawn from the total population of senior high
school students in that school.
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
 Systematic Random Sampling - follows specific steps and procedures
in doing the random selection of the samples. It requires a list of the
elements and every nth element in the list is drawn for inclusion in the
sample. If for instance, you have a list of 5,000 persons and you need a
sample of 500, here are the steps to follow:
1. Divide the number of elements in the population by the desired
sample size. In this case, you divide 5,000 by 500 which gives a
value of 10.
2. Choose a random number between one and the value you obtained
from step 1. In this example, you choose a number between 1 and
10, let’s say you choose 5.
3. Starting with the number you picked which is 5, you take every tenth
(10th) from step 1 and you use 5 as your starting point. Thus, you
have to select the samples whose numbers are 5, 15, 25, 35, 45
and so on until you reach the desired sample size of 500.
 Stratified Random Sampling - In this type of probability sampling
procedure, the population is divided into two or more mutually exclusive
categories based on your variables of interest in the research study. The
population is organized into homogeneous subsets before drawing the
samples. With stratified random sampling, the population is divided into
subpopulation called strata. If your variable of interest is economic
status based on the family combined income level, you can divide the
population into strata of different income levels (low, average, high
income with specific numerical value of annual family income per level).
When these have been determined, you may draw a sample from each
stratum with a separate draw from each of the different strata. The
sample sizes within the strata can now be determined.
To illustrate the procedure to be followed in this probability sampling,
suppose you are interested in how frequent internet use varies by level
among junior high school students. To explore this inquiry, rather than
taking a simple random sample from the school population you need to
ensure that appropriate number of students are drawn from each level
in proportion to the percentage of the population as a whole.
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
In this example, if there are 1,200 junior high school students, here are
the steps to follow:
 Get the population of junior high school students per level. In this
case, the following data were recorded:
Grade 7
350
Grade 8
300
Grade 9
280
Grade 10
270
TOTAL
1,200
 Divide each number of students per level by the total population of
1200 and then multiply by the desired sample size of 300.
In this case,
Grade 7
350/1200 x300=87.5=88
Grade 8
300/1200 x300=75
Grade 9
280/1200 x300=70
Grade 10
270/1200 x300=67.5=67
TOTAL
300
You can now randomly draw out 88 from Grade 7, 75 samples from
Grade 8, 70 from Grade 9 and 67 from Grade 10. This gives a sample
that represents the whole proportionately per level.
Stratified random sampling is preferred by researchers who want to
study subpopulations where categorization of homogeneous
characteristics of each stratum is being considered.
 Cluster Sampling - It is used when the target respondents in a research
study is spread across geographical location. In this method, the
population is divided into groups called clusters which are
heterogeneous in nature and are mutually exclusive. A random sampling
technique is used on relevant clusters to be included in the study.
2. NON-PROBABILITY SAMPLING PROCEDURES
There are situations when the researcher cannot employ random selection.
In cases where probability sampling is not applicable, you may consider
some non-probability sampling alternatives.
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
Types of Non-Probability Sampling Procedures
 Convenience Sampling - This is a method of selecting samples that
are available and are capable of participating in a research study on a
current issue. This method is sometimes called haphazard or availability
sampling. An example would be conducting a survey or interview on a
captive audience inside a mall or park or school to obtain a quick
response of public opinion on an issue about election of public officials.
 Snowball Sampling - It is a technique where the researcher identifies
a key informant about a research of interest and then asks that
respondent to refer or identify another respondent who can participate
in the study. The identification of the samples follows a multiplier effect,
that is, one person is asked to refer the researcher to another
respondent and so on. This technique is applicable when researchers
find difficulty in locating special numbers of a population. The chain
referral procedure allows the researcher to reach the desired samples.
 Purposive Sampling - It is sometimes called judgmental or subjective
sampling. It employs a procedure in which samples are chosen for a
special purpose. It may involve members of limited group of population.
For example, you want to conduct a study on why Grade 11 students
chose Tech-Voc. track over Academic track. You, therefore, find your
samples and your first question would be “Are you planning to go to the
university?” Those who will say “No” would not be included in the study.
 Quota Sampling - It gathers a representative sample from a group
based on certain characteristics of the population chosen by the
researcher. Usually the population is divided into specific groups.
The main difference between stratified random sampling and quota
sampling can be explained in a way that in quota sampling, you use nonrandom selection
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
WHAT’S MORE
ACTIVITY 1.
Directions. Determine the correct sampling procedure that best
corresponds to the given definition/ situation. Write the answer in your
answer sheet.
1. A researcher is interested in conducting an ethnographic study of
the indigenous group called Mangyans who are living in the island of
Mindoro with a total population of 100,000 belonging to at least 8 ethnic
groupings. They are difficult to locate due to the distance and some
have little contact with the lowlanders. What sampling technique should
the researcher use?
2. What sampling procedure should you employ in this example? If the
specific condition requires for both genders, males and females are to
be represented equally in the sample group, then if 60 representatives
are needed, then you get 30 males and 30 females.
3. You want to know the opinion of senior high school students and
obtain their pinion quickly on no-uniform policy of the school. What is
the most applicable sampling technique should you employ?
4. The primary advantage of this technique is to ensure that cases from
each stratum of the population are given importance as in the other
groupings.
5. It is a process of selection of subgroup as representative of a larger
group.
ACTIVITY 2.
Direction. Using the Slovin’s Formula determine the sample size of the
following scenarios. Write your solution in your answer sheet.
1. Suppose you plan to conduct a study among 1,500 Grade 12
students enrolled in the TVL Track. How many respondents are
needed using a margin of error of 2%?
2. As a researcher, you want to conduct a survey in Libertad National
Vocational School with a total enrolment of 1,700 students. How
many respondents are needed using a margin of error of 4%?
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.
WHAT I CAN DO
Direction: Compute the sample size of the following. Copy the table
and show your solution.
1. Given a population (N) of 10,000, complete the table below using
Slovin’s formula.
Estimate of error (e)
1%
2%
3%
4%
5%
Sample Size (n)
2. A public secondary school wishes to assess the students’ views of
the quality of service of specific offices under student services. The
population of 2,500 students consists of:
Grade Level
7
8
9
10
TOTAL
Population (N)
Sample Size (n)
N=2,500
n=?
Additional Activity
Directions. Compare the probability and nonprobability sampling
procedures in terms of the indicated bases for comparison. Copy the
table and write your answer in it.
Basis for
Comparison
Selection process
Research Design
Presence of bias
Probability
Sampling
Nonprobability
Sampling
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Prieto, N.G., et al. (2017). Practical Research for Senior High School. Quezon City, Manila: Lorimar Publishing, Inc.