This document discusses sampling methods for research. It defines sampling as selecting a representative portion of a population when the full population is too large to study directly. The key advantages of sampling are that it saves time, money and effort compared to studying the entire population. However, sampling requires careful design to ensure the sample is representative and results are accurate. The document outlines various sampling designs including random, stratified, systematic and cluster sampling. It also provides a formula and steps for determining sample size.

1. A D V A N T A G E S
D I S A D V A N T A G E S
P L A N N I N G S A M P L E S U R V E Y
D E T E R M I N A T I O N O F S A M P L E S I Z E
S A M P L E D E S I G N
SAMPLING DESIGN

2. Sampling is applicable if the population of the study is
too large especially the 7Ms – Manpower, Money, Materials,
Machinery, Methods, Moment, and Marketing of the researcher
– are limited. It is advantageous for a researcher to use SAMPLE
SURVEY for it is economical rather than total population.
However, the use of total population is advisable if the
number of subjects is less than 100. If the population is equal to
or more than 100, it is advisable to get the sample in order to be
effective, efficient, and economical in gathering data, provided
however, that the sample is a representative cross-section of the
population and is scientifically selected.
SAMPLING DESIGNS

3. SAMPLING. May be defined as the method of getting a
representative portion of a population.
POPULATION. Is the aggregate or total of objects,
persons, families, species, or orders of plants or
animals.

4. The advantages of sampling are as follows:
1. It saves time, money, and effort. The researcher can
save time, money, and effort because the number of
subjects involved is small.
2. It is more effective. Sampling is more effective if
every individual of the population without bias has an
equal chance of being included in the sample and data
are scientifically collected, analyzed, and interpreted.
ADVANTAGES OF SAMPLING

5. 3.It is faster, cheaper, and economical. Since sample is
only “drop in a bucket,” the collection, tabulation,
presentation, analysis and interpretation of data are
rapid and less expensive due to small number of
subjects and few copies of the questionnaires are used.

6. 4. It is more accurate. Fewer errors are made due to
small size of data involved in collection, tabulation,
presentation, analysis, and interpretation.
5. It gives more comprehensive information. Since
there is a thorough investigation of the study due to
small sample, the results give more comprehensive
information because all members of the population
have an equal chance of being included in the sample.

7. If sampling design has strength, it also has its
weaknesses. The disadvantages of sampling are as
follows:
1. Sample data involve more care in preparing detailed
subclassification due to small number of subjects.
2. If the sampling plan is not correctly designed and
followed, the results may be misleading.
3. Sampling requires an expert to conduct the study in
an area. If this is lacking, the results can be erroneous.
DISADVANTAGES OF SAMPLING

8. 4. The characteristics to be observed may occur rarely
in a population, for instance, teachers over 30 years of
teaching experience or teachers with outstanding
performance.
5. Complicated sampling plans are laborious to
prepare.

9. PLANNING SAMPLE SURVEY
The steps in planning a sampling survey
are as follows:
1. State the objectives of the survey.
2. Define the population.
3. Select the sampling individual.
4. Locate and select the source list of particular
individuals to be included in the sample.
5. Decide the sampling design to be used that suits to
the study, either scientific or nonscientific sampling.

10. 6. Determine the sample size by using the formula,
𝑆𝑆 =
𝑁𝑉 + 𝑆𝑒2
1 − 𝑝
𝑁𝑆𝑒 + 𝑉2𝑝 1 − 𝑝
Where: Ss stands for sample size;
N, the population
V, standard value (2.58) of 1 percent
level of probability with 0.99 reliability level
Se, sampling error (0.01)
P, the largest possible proportion
(0.50)

11. 7. Select the method in estimating the reliability of the
sample either test-retest, split-half, parallel-forms, or
internal consistency.
8. Test the reliability of the sample in pilot institution.
9. Interpret the reliability of the sample.
10. Choose experts to administer the research
instruments.

12. DETERMINATION OF SAMPLE SIZE
DETERMINATION OF SAMPLE SIZE
𝑆𝑆 =
𝑁𝑉 + 𝑆𝑒2 1 − 𝑝
𝑁𝑆𝑒 + 𝑉2𝑝 1 − 𝑝
Where: Ss stands for sample size;
N, the population
V, standard value (2.58) of 1 percent level of
probability with 0.99 reliability level
Se, sampling error (0.01)
p, the largest possible proportion (0.50)

13. SAMPLE DESIGNS
SAMPLE DESIGNS
Generally, there are two kinds of sampling
design. These are (1) scientific sampling, and (2) non-
scientific sampling.
In scientific sampling, each member in the
population is given an equal chance of being included
in the sample. In non-scientific sampling, not all of the
members in the population are given an equal chance
of being included in the sample.

14. SCIENTIFIC SAMPLING
1. RESTRICTED RANDOM SAMPLING. This type of
sampling design involves certain restrictions intended to
improve the validity of the sample. However, this design is
applicable only when the population being investigated is
homogeneous. Restricted random samples drawn from a
homogeneous population are likely to arrive at accurate
values of the population characteristics.
2. UNRESTRICTED RANDOM SAMPLING. This is the best
random sampling design due to no restrictions imposed, and
every member in the population has an equal chance of
inclusion in the sample.
 LOTTERY TECHNIQUE
 TABLE OF RANDOM NUMBERS

15. 3. STRATIFIED RANDOM SAMPLING. This type of design
divides first the population into two or more strata. For each
stratum, the sample items are drawn at random.
4. SYSTEMATIC SAMPLING. The individuals in the
population are arranged in a methodical manner, for
instance, alphabetical or chronological (age,
experience or academic rank), and the nth name may
be selected in the construction of the sample.

16. 5. MULTISTAGE SAMPLING. This design is done in
several stages. It can be two-stage, three-stage, four-
stage, and many others depending on the number of
sampling to be used
6. CLUSTER SAMPLING. The population is grouped
into clusters or small units.

17. NON-SCIENTIFIC SAMPLING
1. PURPOSIVE SAMPLING. Based on selecting the
individuals as samples according to the purposes of the
researcher as his controls. An individual is selected as part
of the sample due to good evidence that he is a
representative of the total population.
2. INCIDENTAL SAMPLING.” Is applied to those samples
which are taken because they are the most available.”
(Guilford and Fruchter, 1973)
3. QUOTA SAMPLING. This type of design in the field of
opinion research because it is done by merely looking for
individuals with the requisite characteristics.