A STUDY ON PURPOSIVE SAMPLING METHOD IN RESEARCH

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A STUDY ON PURPOSIVE SAMPLING METHOD IN
RESEARCH

Neetij Rai

Bikash Thapa
CHAPTER I: INTRODUCTION
1.1 GENERAL BACKGROUND
Research is a scientific process of investigation and experimentation that involves the systematic
collection, analysis and interpretation of data to answer a certain question or solve problem.1
Hence, being systematic it has certain methods and techniques to gather the information.
Gathering those information is not always easy as the researcher has to go through huge pile of
information be it primary or secondary. Thus, in such situation it would be practically very
difficult for the researcher to perform the task. Hence, methods like sampling is used when the
universe is very broad and among many of its type purposive sampling method is one of the
widely used method where the researcher has a very important role to play.
1.2 RATIONALE
The main objective of this paper is to explore the concept of purposive sampling method in
research.
1.3 LIMITATION
This paper is only limited to purposive sampling method in research.
1.4 METHODOLOGY
The paper is based on doctrinal research method. The citation rule in the study has been applied
as per Kathmandu School of Law Style Guide to academic writing.

Section Officer, Supreme Court of Nepal / L.L.M.(Ongoing) Kathmandu School of Law.

Advocate/ Rule of Law Advisor, L.L.M. Loyola University, Chicago School of Law.
1
Anand Ballabh Joshi, Megha Raj Banjara, Research Methods and Thesis Writing, Format Printing Press,
Kathmandu, 2004, p. 1.

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CHAPTER II
2.1 GENERAL OVERVIEW OF SAMPLING METHOD
When a small group is selected as representative of the whole it is known as sample method. The
method of selecting for study the portion of universe with a view to draw conclusions about the
universe is called sampling.2
Sampling method refers to the way that observations are selected
from a population to be in the sample for a sample survey.3
Hence, sampling is a process used in statistical analysis in which a predetermined number of
observations will be taken from a larger population.4
As per Goode and Hatt, a sample is a “
smaller representation of large whole.” Nan Lin defines it as “ a subject of cases from the
population chosen to represent it”. Thus, the whole group from which the sample has been drawn
is known as ‘universe’ or ‘population’ and the group selected for study is known as sample.
Sampling is used when,5
i. The researcher has to collect information from a wider area.
ii. The researcher does not require cent percent accuracy.
iii. The population is homogenous
iv. It is not possible to adopt census method.
Assumptions underlying in sampling6
a. Homogeneity amidst complexity:
Although there is complexity in socio-legal phenomena, there appears dominantal unity
in diversity. The assumption is that there is possibility of representative types in the
whole population that makes sampling possible. If no two units were alike in any respect
the sampling would have been impossible.
b. Possibility of representative selection:
2
S.R.Myneni, Legal Research Methodology, Reprint 3rd
edn, Allahabad Law Agency, Haryana, 2007, p. 124.
3
Survey Sampling Methods, available at http://stattrek.com/survey-research/sampling-methods.aspx?Tutorial=AP,
accessed on June 14, 2015.
4
Sampling, available at http://www.investopedia.com/terms/s/sampling.asp#ixzz3edivEXZy, accessed on
5
Myneni (n 2), p. 125.
6
Ibid.

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The assumption is that it is possible to draw a representative sample. If a certain number
of units are selected from a mass on purely random basis, every unit will have a chance of
being included and the sample so selected will contain all types of units, so that it may be
representative.
c. Absolute accuracy not essential:
The assumption is that absolute accuracy is not essential. The 95% of relative accuracy is
fairly sufficient in large scale studies.
d. Independency or interchangeability:
All the items in a sample should be independent of each other.
Characteristics of a Good Sample Design:7
i. Sample design must result in a truly representative sample.
ii. It must be such which results in a small sampling error.
iii. It must be viable in the context of funds available for the research study.
iv. It must be such so that systematic bias can be controlled in a better way.
v. Sample should be such that the results of the sample study can be applied, in general,
for the universe with a reasonable level of confidence.
Process used in Sampling:
1. Identify the population of interest8
A population is the group of people that you want to make assumptions about. For
example, if I want to know how much stress college students experience during
finals. My population is every college student in the world because that's what I am
interested in. Of course, there's no way that I can feasibly study every college student
in the world, so I move on to the next step.
2. Specify a sampling frame9
7
C.R.Kothari, Research Methodology: Methods & Techniques, Revised 2nd
edn, New Age International Publishers,
New Delhi, 2007, p. 58.
8
What is Sampling in Research? - Definition, Methods & Importance, available at
http://study.com/academy/lesson/what-is-sampling-in-research-definition-methods-importance.html, accessed on
June 14, 2015.

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A sampling frame is the group of people from which you will draw your sample. For
example, I might decide that her sampling frame is every student at the university
where I study. Notice that a sampling frame is not as large as the population, but it's
still a pretty big group of people. I still won't be able to study every single student at
her university, but that's a good place from which to draw my sample.
3. Specify a sampling method10
There are basically two ways to choose a sample from a sampling frame: randomly or
non-randomly.
Random sampling, also known as probability sampling or chance sampling is when
every item of the universe has an equal chance of inclusion in the sample. It has
following types:
a. Random Sampling
b. Systematic Sampling
c. Stratified random Sampling
d. Cluster Sampling
Non random sampling, also known as non-probability sampling is a method where
sample is not based on the probability with which a unit can enter the sample but by
other consideration such as common sense, experience, intention and expertise of the
sampler. It has following types:
a. Representative Sampling
b. Accidental Sampling
c. Purposive Sampling
4. Determine the sample size11
In general, larger samples are better, but they also require more time and effort to
manage. If I end up having to go through 1,00 surveys, it will take her more time
9
Ibid.
10
Ibid.
11
Ibid.

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than if I only go through 10 surveys. But the results of my study will be stronger
with 1,00 surveys, so I (like all researchers) has to make choices and find a
balance between what will give me good data and what is practical.
5. Implement the plan12
Once you know your population, sampling frame, sampling method, and sample
size, you can use all that information to choose your sample.
2.2 UNDERSTANDING PURPOSIVE SAMPLING METHOD
 Meaning
Purposive sampling represents a group of different non-probability sampling techniques. Also
known as judgmental, selective or subjective sampling, purposive sampling relies on the
judgement of the researcher when it comes to selecting the units (e.g., people,
cases/organisations, events, pieces of data) that are to be studied. Usually, the sample being
investigated is quite small, especially when compared with probability sampling techniques.13
It is a form of non-probability sampling in which decisions concerning the individuals to be
included in the sample are taken by the researcher, based upon a variety of criteria which may
include specialist knowledge of the research issue, or capacity and willingness to participate in
the research.14
According to Adolph Jenson, “ A purposive selection denotes the method of selecting a number
of groups of units in such a way that selected groups together yield as nearly as possible the
same average or proportion as the totality with respect of those characteristics which are already
a matter of statistical knowledge.”15
Unlike the various sampling techniques that can be used under probability sampling (e.g., simple
random sampling, stratified random sampling, etc.), the goal of purposive sampling is not to
12
Ibid.
13
Purposive sampling, available at http://dissertation.laerd.com/purposive-sampling.php , accessed on June 15, 2015
14
Paul Oliver, Purposive sampling, available at http://srmo.sagepub.com/view/the-sage-dictionary-of-social-
research-methods/n162.xml, accessed on June 15, 2015.
15
Myneni (n 2), p. 125.

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randomly select units from a population to create a sample with the intention of making
generalisations (i.e., statistical inferences) from that sample to the population of interest. This is
the general intent of research that is guided by a quantitative research design.16
The main goal of purposive sampling is to focus on particular characteristics of a population that
are of interest, which will best enable you to answer your research questions. The sample being
studied is not representative of the population, but for researchers pursuing qualitative or mixed
methods research designs, this is not considered to be a weakness. Rather, it is a choice, the
purpose of which varies depending on the type of purposing sampling technique that is used. For
example, in homogeneous sampling, units are selected based on their having similar
characteristics because such characteristics are of particular interested to the researcher. By
contrast, critical case sampling is frequently used in exploratory, qualitative research in order to
assess whether the phenomenon of interest even exists (amongst other reasons).
Purposive sample is a non-representative subset of some larger population, and is constructed to
serve a very specific need or purpose. A researcher may have a specific group in mind, such as
high level business executives.17
 Types of Purposive Sampling
1. Maximum variation sampling18
Maximum variation sampling, also known as heterogeneous sampling, is a purposive
sampling technique used to capture a wide range of perspectives relating to the thing that
researchers are interested in studying; that is, maximum variation sampling is a search for
variation in perspectives, ranging from those conditions that are view to be typical through to
those that are more extreme in nature. By conditions, it mean the units (i.e., people,
cases/organisations, events, pieces of data) that are of interest to the researcher. These units
may exhibit a wide range of attributes, behaviours, experiences, incidents, qualities,
situations, and so forth. The basic principle behind maximum variation sampling is to gain
16
Purposive sampling, (n 13).
17
Types of samples, available at
http://psychology.ucdavis.edu/faculty_sites/sommerb/sommerdemo/sampling/types.htm, accessed on June 16, 2015.
18
Purposive Sampling, (n 13).

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greater insights into a phenomenon by looking at it from all angles. This can often help the
researcher to identify common themes that are evident across the sample.
2. Homogeneous sampling19
Homogeneous sampling is a purposive sampling technique that aims to achieve a
homogeneous sample; that is, a sample whose units (e.g., people, cases, etc.) share the same
(or very similar) characteristics or traits (e.g., a group of people that are similar in terms of
age, gender, background, occupation, etc.). In this respect, homogeneous sampling is the
opposite of maximum variation sampling. A homogeneous sample is often chosen when the
research question that is being address is specific to the characteristics of the particular group
of interest, which is subsequently examined in detail.
3. Typical case sampling20
Typical case sampling is a purposive sampling technique used when you are interested in the
normality/typicality of the units (e.g., people, cases, events, settings/contexts, places/sites)
you are interested, because they are normal/typical. The word typical does not mean that the
sample is representative in the sense of probability sampling (i.e., that the sample shares the
same/similar characteristics of the population being studied). Rather, the word typical means
that the researcher has the ability to compare the findings from a study using typical case
sampling with other similar samples (i.e., comparing samples, not generalising a sample to a
population). Therefore, with typical case sampling, you cannot use the sample to make
generalisations to a population, but the sample could be illustrative of other similar samples..
4. Extreme (or deviant) case sampling21
Extreme (or deviant) case sampling is a type of purposive sampling that is used to focus on
cases that are special or unusual, typically in the sense that the cases highlight notable
19
Ibid.
20
Ibid.
21
Ibid.

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outcomes, failures or successes. These extreme (or deviant) cases are useful because they
often provide significant insight into a particular phenomenon, which can act as lessons (or
cases of best practice) that guide future research and practice. In some cases, extreme (or
deviant) case sampling is thought to reflect the purest form of insight into the phenomenon
being studied.
5. Critical case sampling22
Critical case sampling is a type of purposive sampling technique that is particularly useful in
exploratory qualitative research, research with limited resources, as well as research where a
single case (or small number of cases) can be decisive in explaining the phenomenon of
interest. It is this decisive aspect of critical case sampling that is arguably the most important.
To know if a case is decisive, think about the following statements: ?If it happens there, it
will happen anywhere?; or ?if it doesn?t happen there, it won?t happen anywhere?; and ?If
that group is having problems, then we can be sure all the groups are having problems?.
Whilst such critical cases should not be used to make statistical generalisations, it can be
argued that they can help in making logical generalisations. However, such logical
generalisations should be made carefully.
6. Total population sampling23
Total population sampling is a type of purposive sampling technique where you choose to
examine the entire population (i.e., the total population) that have a particular set of
characteristics (e.g., specific experience, knowledge, skills, exposure to an event, etc.). In
such cases, the entire population is often chosen because the size of the population that has
the particular set of characteristics that you are interest in is very small. Therefore, if a small
number of units (i.e., people, cases/organisations, etc.) were not included in the sample that is
investigated, it may be felt that a significant piece of the puzzle was missing [see the article,
Total population sampling, to learn more].
22
Ibid.
23
Ibid.

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7. Expert sampling24
Expert sampling is a type of purposive sampling technique that is used when your research
needs to glean knowledge from individuals that have particular expertise. This expertise may
be required during the exploratory phase of qualitative research, highlighting potential new
areas of interest or opening doors to other participants. Alternately, the particular expertise
that is being investigated may form the basis of your research, requiring a focus only on
individuals with such specific expertise. Expert sampling is particularly useful where there is
a lack of empirical evidence in an area and high levels of uncertainty, as well as situations
where it may take a long period of time before the findings from research can be uncovered.
Therefore, expert sampling is a cornerstone of a research design known as expert elicitation.
 Advantages of Purposive Sampling
1. One of the major benefits of purposive sampling is the wide range of sampling techniques
that can be used across such qualitative research designs; purposive sampling techniques
that range from homogeneous sampling through to critical case sampling, expert
sampling, and more.
2. Whilst the various purposive sampling techniques each have different goals, they can
provide researchers with the justification to make generalisations from the sample that is
being studied, whether such generalisations aretheoretical, analytic and/or logical in
nature. However, since each of these types of purposive sampling differs in terms of the
nature and ability to make generalisations, you should read the articles on each of these
purposive sampling techniques to understand their relative advantages.
3. Qualitative research designs can involve multiple phases, with each phase building on the
previous one. In such instances, different types of sampling technique may be required at
each phase. Purposive sampling is useful in these instances because it provides a wide
range of non-probability sampling techniques for the researcher to draw on. For
example, critical case sampling may be used to investigate whether a phenomenon is
worth investigating further, before adopting an expert sampling approach to examine
specific issues further.
24
Ibid.

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4. Proper care will be taken in selecting the sample.
5. At times, this method is less expensive and less time consuming.
6. It is very useful when some of the units are very important and must be included.
 Disadvantages of Purposive Sampling
1. Purposive samples can be highly prone to researcher bias. The idea that a purposive
sample has been created based on the judgement of the researcher is not a good defence
when it comes to alleviating possible researcher biases, especially when compared
with probability sampling techniques that are designed to reduce such biases. However,
this judgemental, subjective component of purpose sampling is only a major disadvantage
when such judgements are ill-conceived or poorly considered; that is, where judgements
have not been based on clear criteria, whether a theoretical framework, expert elicitation,
or some other accepted criteria.
2. The subjectivity and non-probability based nature of unit selection (i.e., selecting people,
cases/organisations, etc.) in purposive sampling means that it can be difficult to defend
the representativeness of the sample. In other words, it can be difficult to convince the
reader that the judgement you used to select units to study was appropriate. For this
reason, it can also be difficult to convince the reader that research using purposive
sampling achieved theoretical/analytic/logical generalisation. After all, if different units
had been selected, would the results and any generalisations have been the same?
3. The knowledge of population may not always be available. If this happens then the
researcher cannot fully use the method.

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CHAPTER III: CONCLUSION
Redman and Mory described research as “systematized effort to gain knowledge”. Hence,
research is undertaken with the purpose to arrive at a state of generality.25
But the universe is so
vast that it would be almost impossible for the researcher to go through all the units. Thus,
sampling method is employed due to which the researcher is able to provide a valid analysis even
in this vast universe. Among various types of sampling method, purposive sampling is also one
of them. Some types of research design necessitate researchers taking a decision about the
individual participants who would be most likely to contribute appropriate data, both in terms of
relevance and depth. For example, in life history research, some potential participants may be
willing to be interviewed, but may not be able to provide sufficiently rich data.
In sampling, a small, but carefully chosen sample can be used to represent the population.26
The
sample reflects the characteristics of the population from which it is drawn. Purposive sampling
seems to be more appropriate when the universe happens to be small and a known characteristic
of it is to be studied intensively. It starts with a purpose in mind and the sample is thus selected
to include people of interest and exclude those who do not suit the purpose.27
Purposive method gives more leverage to the researcher to perform and bring out the best
information possible from the samples and it depends on the knowledge, judgment and intellect
of the researcher to a large extent. Hence, despite having some limitations, purposive sampling
is the only possible solution when some of the units are very important cannot be missed out.
25
Myneni (n 2), p. 1.
26
Survey Sampling Methods, available at https://www.statpac.com/surveys/sampling.htm, accessed on June 16,
2015.
27
Purposive Sampling, available at
http://changingminds.org/explanations/research/sampling/purposive_sampling.htm , accessed on June 16, 2015.

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BIBILOGRAPHY
Joshi, Anand Ballabh, Banjara, Megha Raj Research Methods and Thesis Writing, Format
Printing Press, Kathmandu, 2004.
Kothari, C.R Research Methodology: Methods & Techniques, Revised 2nd
edn, New Age
International Publishers, New Delhi, 2007.
Myneni, S.R. Legal Research Methodology, Reprint 3rd
edn, Allahabad Law Agency, Haryana,
2007.
Oliver, Paul, Purposive sampling, available at http://srmo.sagepub.com/view/the-sage-
dictionary-of-social-research-methods/n162.xml
Purposive Sampling, available at
http://changingminds.org/explanations/research/sampling/purposive_sampling.htm
Purposive sampling, available at http://dissertation.laerd.com/purposive-sampling.php
Sampling, available at http://www.investopedia.com/terms/s/sampling.asp#ixzz3edivEXZy,
Survey Sampling Methods, available at http://stattrek.com/survey-research/sampling-
methods.aspx?Tutorial=AP
Survey Sampling Methods, available at https://www.statpac.com/surveys/sampling.htm,
Types of samples, available at
http://psychology.ucdavis.edu/faculty_sites/sommerb/sommerdemo/sampling/types.htm
What is Sampling in Research? - Definition, Methods & Importance, available at
http://study.com/academy/lesson/what-is-sampling-in-research-definition-methods-
importance.html

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