Sampling involves selecting a subset of individuals or data points from within a population to gather insights about that population. There are two main types of sampling: probability sampling, where each member of the population has a known, non-zero chance of being selected; and non-probability sampling, where selections are made in a non-random manner. Some common sampling methods include simple random sampling, stratified random sampling, cluster sampling, systematic sampling, convenience sampling, purposive sampling, and quota sampling. The size and type of sample needed depends on factors like the population size, desired confidence level, and goals of the research.

1. research sampling

2. Sampling is the process
of selecting observations
(a sample) to provide an
adequate description
and inferences of the
population.

3. Sampling is the process
of selecting a number of
individuals for a study in
such a way that the
individuals represent the
larger group from which
they were selected.

4. Sampling is the act,
process, or technique of
selecting a suitable sample,
or a representative part of
a population for the
purpose of determining
parameters or
characteristics of the whole
population.

5. 5
sampling
target population
study population
sample

6. A sample is “a smaller
(but hopefully
representative) collection
of units from a
population used to
determine truths about
that population” (Field, 2015)
research sampling

7. research sampling
Population is the larger
group from which
individuals are selected to
participate in a study

8. SAMPLING BREAKDOWN
All universities in the Philippines
All universities in Cebu
List of Cebu universities
Three universities in Cebu

9. • When it’s impossible to study the whole population
why just a sample?
• Cost efficient
• More accuracy of results
• High speed of data collection
• Availability of Population elements.
• Less field time

10. The sample must be:
what is a good sample?
representative of the population;
appropriately sized;
unbiased;
random.

11. Stages in the
Selection
of a Sample

12. quantitative
sampling

13. quantitative
sampling
probability
sampling
non-probability
sampling

15. probability
sampling
simple
random
stratified
random
cluster systematic

16. simple random sampling
Applicable when population is small,
homogeneous & readily available

17. simple random sampling
Selecting subjects so that all members of a
population have an equal and independent
chance of being selected.

18. simple random sampling
All subsets of the frame are given an equal
probability. Each element of the frame has an
equal probability of selection. A table of
random number or lottery system is used to
determine which units are to be selected.

19. simple random sampling
Advantages
• Easy method to use
• No need of prior information of population
• Equal and independent chance of selection to
every element
• High probability of achieving a representative
sample
• Meets assumptions of many statistical
procedures

20. simple random sampling
Disadvantages
• If sampling frame large, this method
impracticable.
• Does not represent proportionate
representation
• Identification of all members of the
population can be difficult
• Identifying members of all subgroups can be
difficult

21. selecting random samples
Define
population
Develop
sampling
frame
Assign
each unit a
number
Randomly
select the
required
amount of
random
numbers
Systematically
select random
numbers until
it meets the
sample size
requirements
Sunil Kumar

22. simple random sampling
Every subset of a specified size n from the population
has an equal chance of being selected
Sunil Kumar

23. stratified random sampling
The population is divided into two or
more groups, called strata, according
to some criterion, such as geographic
location, grade level, age, or income,
and subsamples are randomly selected
from each strata.

24. stratified random sampling
Identify and
define the
population
Determine the
desired
sample size
Identify the
variable and
subgroups (i.e.,
strata) for which
you want to
guarantee
appropriate
representation
Classify all
members of the
population as
members of one
of the identified
subgroups

25. stratified random sampling

26. stratified random sampling
Advantages
• More accurate sample
• Can be used for both proportional and non-
proportional samples
• Representation of subgroups in the sample
• Enhancement of representativeness to each
sample
• Higher statistical efficiency
• Easy to carry out

27. stratified random sampling
Disadvantages
• Identification of all members of the
population can be difficult
• Identifying members of all subgroups can be
difficult
• Classification error
• Time consuming and expensive
• Prior knowledge of composition and of
distribution of population

28. The process of randomly selecting intact
groups, not individuals, within the
defined population sharing similar
characteristics
cluster sampling

29. Clusters are locations within which an intact
group of members of the population can be
found.
e.g: neighborhoods
school districts
schools
classrooms
cluster sampling

30. stratified random sampling
Define
population
Develop
sampling
frame
according to
characteristic
s required
Determine
the
proportion of
each
population
variable of
interest
Systematic
sampling
methods can
then be
followed to
select sample
unit

31. cluster sampling
Section 4
Section 5
Section 3
Section 2Section 1
Sunil Kumar

32. cluster sampling

33. Advantages
• Very useful when populations are large and spread
over a large geographic region
• Convenient and expedient
• Do not need the names of everyone in the
population
cluster sampling

34. Disadvantages
• Representation is likely to become an issue
cluster sampling

35. Selecting every Kth subject from a list of the
members of the population
systematic sampling

36. systematic sampling
Define
populatio
n
Develop
sampling
frame
Decide
the
sample
size
Work out
what
fraction of
the frame
the sample
size
represents
Select
according
to fraction
(100 sample
from 1,000
frame then
10% so
every 10th
unit)
First unit
select by
random
numbers
then
every nth
unit
selected
(e.g.
every
10th)

37. systematic sampling
k =
N
n
where
n sample size
N population size
k size of selection interval=
=
=

38. systematic sampling
Example:
To select a sample of 25 dorm rooms in your college dorm,
makes a list of all the room numbers in the dorm. For example
there are 100 rooms, divide the total number of rooms (100) by
the number of rooms you want in the sample (25). The answer is
4. This means that you are going to select every fourth dorm
room from the list. First of all, we have to determine the random
starting point. This step can be done by picking any point on the
table of random numbers, and read across or down until you
come to a number between 1 and 4. This is your random starting
point. For instance, your random starting point is "3". This means
you select dorm room 3 as your first room, and then every fourth
room down the list (3, 7, 11, 15, 19, etc.) until you have 25 rooms
selected.

39. systematic sampling

40. systematic sampling

41. Advantage
• Very easily done
Disadvantages
• Subgroups
• Some members of the population don’t
have an equal chance of being included
systematic sampling

42. According to Uma Sekaran in
Research Method for Business (4th
Ed, 2010), Roscoe proposed the
rules of thumb for determining
sample size where sample size
larger than 30 and less than 500
are appropriate for most research,
and the minimum size of sample
should be 30% of the population.

43. The size of the sample depends
on a number of factors and the
researchers have to give the
statistically information before
they can get an answer. For
example, these information like
(confidence level, standard
deviation, margin of error and
population size) to determine
the sample size.

44. non-probability
sampling
convenience purposive quota

45. convenience sampling
Also called “grab”, “opportunity”,
“accidental” or “haphazard” sampling

46. convenience sampling
It the process of including whoever happens
to be available at the time

47. convenience sampling
It is most useful for pilot testing.

48. convenience sampling
Advantage
A sample selected for ease of access, immediately
known population group and good response rate.

49. convenience sampling
Disadvantage
Cannot generalise findings (do not know what
population group the sample is representative of) so
cannot move beyond describing the sample.

50. convenience sampling
Disadvantage
Difficulty in determining how much of the effect
(dependent variable) results from the cause
(independent variable)

51. convenience sampling
Disadvantage
•Problems of reliability
•Do respondents represent the target population?
•Results are not generalizable

52. purposive sampling
The process whereby the researcher selects a
sample based on experience or knowledge of
the group to be sampled

53. purposive sampling
Also called “judgment” sampling

54. purposive sampling
The researcher chooses the sample based on
who they think would be appropriate for the
study.

55. purposive sampling
Advantage
Based on the experienced person’s judgment
Disadvantage
Cannot measure the representativeness of the
sample

56. The process whereby a researcher gathers
data from individuals possessing
identified characteristics and quotas
quota sampling

57. PROCESS
• The population is first segmented into mutually
exclusive sub-groups, just as in stratified
sampling.
• Then judgment used to select subjects or units
from each segment based on a specified
proportion.
• For example, an interviewer may be told to
sample 200 females and 300 males between the
age of 45 and 60.
quota sampling

58. In quota sampling the selection of the
sample is non-random.
quota sampling

59. Advantages
• Contains specific subgroups in the proportions
desired
• May reduce bias
• Easy to manage, quick
quota sampling

60. Disadvantages
• Dependent on subjective decisions
• Not possible to generalize
• Only reflects population in terms of the quota,
possibility of bias in selection, no standard
error
quota sampling

61. sampling in
qualitative research

62. Researchers in qualitative
research select their
participants according to their:
• characteristics
• knowledge

63. Purposeful sampling is when
the researcher chooses persons
or sites which provide specific
knowledge about the topic of
the study.

64. Types of Purposeful Sampling
1) Maximal Variation Sampling
2) Typical Sampling
3) Theory or Concept Sampling
4) Homogeneous Sampling
5) Critical Sampling
6) Opportunistic Sampling
7) Snowball Sampling

65. Types of Purposeful Sampling
1) Maximal Variation Sampling
2) Typical Sampling
3) Theory or Concept Sampling
4) Homogeneous Sampling
5) Critical Sampling
6) Opportunistic Sampling
7) Snowball Sampling

66. 1- Maximal Variation Sampling
It is when you select individuals that
differ on a certain characteristic. In this
strategy you should first identify the
characteristic and then find individuals
or sites which display that
characteristic.

67. It is when you study a person or a site
that is “typical” to those unfamiliar with
the situation. You can select a typical
sample by collecting
demographic data or survey data
about all cases.
2- Typical Sampling

68. 3-Theory or Concept Sampling
It is when you select individuals or sites
because they can help you to generate a
theory or specific concepts within the
theory. In this strategy you need a full
understanding of the concept or the theory
expected to discover during the study.

69. 4- Homogeneous Sampling
It is when you select certain sites or
people because they possess similar
characteristics. In this strategy, you
need to identify the characteristics and
find individuals or sites that possess it.

70. 5- Critical Sampling
It is when you study an
exceptional case represents the
central phenomenon in dramatic
terms.

71. 6- Opportunistic Sampling
It is used after data collection
begins, when you may find that
you need to collect new
information to answer your
research questions.

72. 7- Snowball Sampling
It is when you don't know the best people
to study because of the unfamiliarity of the
topic or the complexity of events. So you
ask participants during interviews to
suggest other individuals to be sampled.

73. • It is the researcher’s ethical responsibility to
safeguard the story teller by maintaining the
understood purpose of the research…
• The relationship should be based on trust
between the researcher and participants.
• Inform participants of the purpose of the
study.
Ethical Considerations in Data
Collection

74. • Being respectful of the research site,
reciprocity, using ethical interview
practices, maintaining privacy, and
cooperating with participants.
• Patton (2002) offered a checklist of
general ethical issues to consider, such
as:
 reciprocity
 assessment of risk
confidentiality,
informed consent
 and data access and ownership.

75. • Qualitative researchers must
be aware of the potential for
their own emotional turmoil in
processing this information
• During the interview process,
participants may disclose
sensitive and potentially
distressing information in the
course of the interview..

76. The respondents of the study were thirty (30)
PNP personnel of Iloilo City Police Office who were
assigned at Women and Children Protection Desks.
Total enumeration sampling technique or all
members of the population were participants of this
research. It has a high level of accuracy and
provides a complete statistical coverage over space
and time.
The respondents of the study were made
aware of the nature and purpose of this study and
that the identities of the respondents and data
collected would be completely confidential. (cont’d)
Monsale, Sharon S. (2016) Level of emotional empathy among women and children protection desk
personnel (Unpublished Thesis). Iloilo City: WVSU Publishing.

77. The 30 respondents were classified into age,
civil status, and length of service. As to age, 90%
(n=27) were younger, while 10% (n=3) were older.
As to civil status, 46.67% (n=14) were married, while
53.33% (n=16) were single. As to length of service,
60% (n=18) were classified in longer years, while
40% (n=12) were classified in shorter years.
Monsale, Sharon S. (2016) Level of emotional empathy among women and children protection desk
personnel (Unpublished Thesis). Iloilo City: WVSU Publishing.

78. The subject of the study is a 5-year old child
with hearing impairment and is currently enrolled in
San Joaquin, Iloilo. The subject was chosen by the
researchers.
Gaitan, L.M.B., Mediodia, M.C.A., Tabaquirao, M.J.T., Tabuga, K.F.B., Varon, M.L.T. (2014) Visual
approach in teaching functional sign language to a 5-year-old child with hearing impairment.
(Unpublished undergraduate thesis). Iloilo City: WVSU Publishing.

79. The stratified random sampling was used to
determine the number of participants using the
Slovin’s Equation to obtain a good representative
sample with 0.05 margin of error.
The fishbowl method was used to choose the
14 participants from elementary, 16 from
secondary, and 37 from the tertiary levels.
Sembran, S.J. (2010) Interpersonal conflict management styles of administrators and teachers in a
private sectarian school. (Unpublished master’s thesis). Iloilo City: WVSU Publishing.

80. The respondents of the study were the pre-
service teachers of West Visayas State University-
Janiuay Campus who are duly enrolled for the
second semester 2011-2012. They were grouped
according to course, sex and GPA. They were
identified through stratified random sampling.
There were 80 respondents who are the pre-
service teachers of West Visayas State University-
Janiuay Campus. These respondents were classified
into course, sex and GPA. (cont’d)
Pendon, G.P. (2012) Awareness of peace education knowledge, attitudes, values and skills (KAVS) of
pre-service teachers. (Unpublished master’s thesis). Iloilo City: WVSU Publishing.

81. As to course, 75% (n=60) were Bachelor in
Elementary Education (BEED), while 25% (n=20)
were Bachelor in Secondary Education (BSED). As to
sex, 82.5% (n=66) were females and 17.5% (n=14)
were males. When classified as to GPA, 12.5 %
(n=10) respondents had high GPA, 77.5% (n=62)
had average GPA and 10% (n=8) had low GPA.
Pendon, G.P. (2012) Awareness of peace education knowledge, attitudes, values and skills (KAVS) of
pre-service teachers. (Unpublished master’s thesis). Iloilo City: WVSU Publishing.

82. As to course, 75% (n=60) were Bachelor in
Elementary Education (BEED), while 25% (n=20)
were Bachelor in Secondary Education (BSED). As to
sex, 82.5% (n=66) were females and 17.5% (n=14)
were males. When classified as to GPA, 12.5 %
(n=10) respondents had high GPA, 77.5% (n=62)
had average GPA and 10% (n=8) had low GPA.
Pendon, G.P. (2012) Awareness of peace education knowledge, attitudes, values and skills (KAVS) of
pre-service teachers. (Unpublished master’s thesis). Iloilo City: WVSU Publishing.

83. Subjected to analysis and comparison in this
study were the banner headlines of the student
publications of each of the seven colleges in the
main campus of West Visayas State University.
Identified for analysis and comparison were the
purposively selected most recent publications but
not earlier than issues published during the school
year 2011-2012.
Paragados, J.C. (2014) Content analysis of front-page banner headlines of college publications in a
state university. (Unpublished master’s thesis). Iloilo City: WVSU Publishing.