Non-probability sampling is a type of sampling where samples are gathered in a way that does not give all individuals in the population an equal chance of being selected. It is often used when random sampling is impossible due to large population sizes or limited resources. Some common types of non-probability sampling include convenience sampling, quota sampling, snowball sampling, and purposive sampling. While non-probability sampling is less costly and easier than probability sampling, the results cannot be generalized to the larger population due to potential sampling biases.

2. Non-probability sampling

3. INTRODUCTION
 Sampling is a process of selecting representative units from
an entire population of a study. Sampling is not a new
development, but in recent times it is used by people in all
fields, even in day-to-day life, to get an understanding about
societies, opinions, or situations

4. PURPOSE
 Economical: it is not possible and economical for researchers to study an entire population. With the help of
sampling, the researcher can save lots of time, money, and resources to study a phenomenon.
 Improved quality of data: It is a proven fact that when a person handles less amount of work or fewer number
of people, then it is easier to ensure the quality of the outcome. it is easier to maintain the quality of the
research work, which would not be possible in case the entire population was involved.
 Quick study results: Studying an entire population itself will take a lot of time, and generating research results
of a large mass will be almost impossible as most research studies have time limits. But with a sample, it is
possible to generate study results faster.
 Precision and accuracy of data: Conducting a study on an entire population provides researchers with
voluminous data, and maintaining precision of that data becomes a undersome task, while carrying a study on a
part of the population (sample) helps the researcher to generate more precise data, where formulation of the
interpretations of the data becomes much easier. It is always easy to establish better rapport with a sample and
thus to collect more accurate data.

5. TERMINOLOGY USED IN SAMPLING
 Population: Population is the aggregation of all the units in which a researcher is interested. In
other words, population is the set of people or entities to which the results of a research are to be
generalized.
 Target population: A target population consists of the total number of people or objects which
meet the designated set of criteria. In other words, it is the aggregate of all the cases with a
certain phenomenon (or phenomena) about which the researcher would like to make a
generalization.
 Accessible population: It is the aggregate of cases that conform to designated criteria and are
also accessible as subjects for a study.
 Sampling: Sampling is the process of selecting a representative segment under study.
 Sample: Sample may be defined as representative unit of a target population, which is to be
worked upon by researchers during their study. In other words, sample consists of a subset of
units which comprise the population selected by investigators or researchers to participate in
their research project.

6.  Element: The individual entities that comprise the samples and population are known as elements, and
an element is the most basic unit about whom/which information is collected. An element is also known
as a subject in research. The most common element in nursing research is an individual.
 Sampling frame: It is a list of all the elements or subjects in the population from which the sample is
drawn. Sampling frame could be prepared by the researcher or an existing frame may be used. .
 Sampling error: There may be fluctuations in the values of the statistics of characteristics from one
sample to another, or even those drawn from the same population.
 Sampling bias: Distortion that arises when a sample is not representative of the population from which it
was drawn.
 Sampling plan: The formal plan specifying a sampling method, a sample size, and the procedure of
selecting the subjects.

7. WHY WE NEED SAMPLING
 Sampling makes possible the study of a large, (different
characteristics) population.
 Sampling is for economy
 Sampling is for speed.
 Sampling is for accuracy.
 Sampling saves the sources of data from being all consumed

8. TYPES OF SAMPLING TECHNIQUE
PROBABILITY
SAMPLING
 It is based on the theory of probability. It
involves random selection of the
elements/members of the population. In
this, every subject in a population has equal
chance to be selected as study sample.
Probability sampling technique is used to
enhance the representativeness of the
selected sample for a study. In probability
sampling techniques, the chances of
systematic bias are relatively less because
subjects are randomly selected.
NON- PROBABILITY
SAMPLING
 Non-probability sampling is a technique
wherein the samples are gathered in a
process that does not give all the individuals
in the population equal chances of being
selected in the sample. In other words, in this
type of sampling every subject does not have
equal chance to be selected because
elements are chosen by choice not by chance
through nonrandom sampling methods.

9. FEATURES OF NON-PROBABILITY SAMPLING
 Non-probability sampling is a technique wherein the samples are gathered in a process that does not give
all the individuals in the population equal chances of being selected. In any form of research, true random
sampling is always difficult to achieve. .
 Most researchers are bound by time, money, and workforce, and because of these limitations, it is difficult
to randomly sample the entire population and it is employ another sampling technique, the non-probability
sampling technique, the non - probability sampling technique.
 In contrast with probability sampling, non-probability sample is not a product of a randomized selection
processes. Subjects in a non-probability sample are usually selected on the basis of their accessibility or by
the purposive personal judgment of the researcher.
 The downside of this is that an unknown proportion of the entire population is not sampled. This entails that
the sample may or may not represent the entire population accurately. Therefore, the results of the
research cannot be used in generalizations pertaining to the entire population.

10. USES OF NON-PROBABILITY SAMPLING
 Non-probability sampling is used in following situations.
 This type of sampling can be utilized when it is needed to show that a particular trait is existent in the
population.
 It can also be utilized when the researcher targets to make a qualitative, pilot, or exploratory study.
 When random sampling is impossible like when the population is almost limitless, it can also be used. .
Moreover, when the research does not aim to produce results that will be utilized to generate
generalizations pertaining to the entire population, it can be used.
 In addition, when the researcher has got limited budget, time, and workforce, it is also of use.
 Used as a random sampling or, probability sampling, this technique can also be used in an initial study
(pilot study) and can be carried out again.

11. TYPES OF NON- PROBABILITY SAMPLING

13. Convenient sampling
 In this methods researcher selects those units of the population in the sample which
appear convenient to him or to the management of the organization where he is
conducting research. The management of the organization may tell the researcher that
certain individuals alone can be included in the sample while others can’t. One
important demerit of this method is that result obtained by the following this method can’t
be generalized beyond the study’s sample. But this doesn’t mean that such study are of
no value. The cumulative result of many such studies of the same phenomenon by
different researchers provide basis of assessing the merits of a given hypothesis.In non-
probability sampling, the investigator can not estimate the probability that each element
of the population will be included in the sample.

14. ADVANTAGES
 Convenience sampling is the cheapest and simplest.
 It does not require a list of population.
 It does not require any statistical expertise.
DISADVANTAGES
 Convenience sampling is highly biased, because of the researcher’s subjectivity, and so it does
not yield a representative sample.
 It is the least reliable sampling method. There is no way of estimating the representativeness
of the sample.
 The findings cannot be generalized.
 Non-probability sampling plan does not perform inferential function i.e. the population
parameters cannot be estimated from the sample values.
 It suffers from sampling bias, which will distort result. Therefore, non-random is not a desirable
method.

15. QUOTA SAMPLING
 “OUOTA SAMPLING is a method of stratified sampling in which selection within strata is non-
random. It is this non random element that constitutes its greater weakness.”
 Quota are stratified by such variables as sex, age, and religion and social class.
 It is easy to classify the accessible respondents under sex, age, social class and religion,
 It is very difficult to classify them into social categories.
 Advantages
 It is considerable less costly then probability sampling
 It takes less time
 There is no need of list of population.
 Field work can be easily organized.

16.  MERITS:
 It is less costly.
 It is administratively easy.
 It is most suited in situation where field work has to be done quickly perhaps in order to
reduce memory errors.
 DEMERITS:
 It is not possible to estimate sampling errors because quota sampling does not meet the basic
requirement of randomness.
 It may not provide a representative sample of respondents despite there being instruction to, and
constraints on, interviewer to guard against the main danger of selection bias.

17. Snowball sampling
 It is also known as nominated sampling, is a non-probability sampling procedure in which
study subjects are asked to provide referrals to other study subjects. In this method of
sampling, investigators identify individual respondents whom they believe to have pertinent
information related to their study. They then ask these individuals to name (nominate) others
who might be able to provide further information; these respondents, in turn, are then asked to
name other potential respondents. This sampling technique is also termed network sampling
or link-tracing sampling.
 This sampling technique may also be used in socio-metric studies. For example, the members
of a social group may be asked to name the persons with whom they have social contacts,
each one of the persons so named may also be asked to do so, and so on. The researcher
may thus get a constellation of associates and analyze it.

18.  Advantages
 It is very useful in studying social groups, informal group in a formal organization, and
diffusion of information among professionals of various kinds.
 It is useful for smaller populations for which no frames are readily available.

 Disadvantages
 It does not allow the use of probability statistical methods. Elements included are
dependent on the subjective choice of the original selected respondents.
 It is difficult to apply this method when the population is large.
 It does not ensure the inclusion of all elements in the list.

19. Purposive or judgement sampling
 Purposive sampling, also termed judge mental sampling, is a type of non-
probability sampling in which subjects are selected because they are identified as
knowledgeable regarding the subject under investigation. The investigator
establishes certain criteria thought to be representative of the target population and
deliberately selects subjects according to these criteria. For example, in
investigating the characteristics of undergraduate nursing students most likely to
succeed in graduate programmes, the investigator might ask persons who are
knowledgeable regarding nursing education either to participate directly in the
study or to recommend students to be selected for the study.

20.  Advantages
 It is very useful in studying social groups, informal group in a formal organization, and
diffusion of information among professionals of various kinds.
 It is useful for smaller populations for which no frames are readily available.
 Disadvantages
 It does not allow the use of probability statistical methods. Elements included are dependent
on the subjective choice of the original selected respondents.
 It is difficult to apply this method when the population is large.
 It does not ensure the inclusion of all elements in the list.

21. Theoretical sampling
 Theoretical sampling is a non-probability approach to sampling most often
associated with qualitative research, primarily the grounded theory method. As the
study data are collected, coded, and analyzed, the researcher examines the
emerging conceptual categories and themes and decides on further data-
collection procedures that have the potential to contribute to the developing
theory. The researcher may change the focus of the research questions, the
locations where the questions are asked, or the participants in the study

22. Voluntary sampling
 Voluntary sampling is a type of non-probability sampling procedure in which
volunteers either offer or are actively recruited to participate in a study.
 A request for volunteers might be made through an international organization
such as the Red Cross (for instance, for a study of couples in prenatal or neonatal
classes) or through solicitation by advertisements in newspapers or journals. The
use of volunteers has the potential to bias the results of a study because those
individuals who did not choose to volunteer might have provided other
perspectives than those of the volunteers.

23. Modal instance sampling
 Modal instance sampling is a type non-probability sample composed of subjects who
represent the "typical case" that is constructed by the researcher for purposes of the
study. The method draws its name from the mode, the most frequently occurring score
or value in a set of measurements. Thus, the mode can be considered to be the typical
case. For example, a researcher planning to use modal instance sampling could
construct a profile of "the typical baccalaureate-prepared nurse" in a specific health
care setting by using the combined qualities of age, education, and years of
professional nursing experience. This information could be gathered through self-
reports or by examining personnel records in the setting that was targeted for the
research. In this instance, the researcher has chosen not to include other personal
qualities such as gender, religion, or ethnicity. Using the modal instance technique, the
researcher would then sample only those individuals who could be described as "the
typical baccalaureate-prepared nurse" for purposes of the study

24. Expert sampling
 Expert sampling is a non-probability sampling procedure in which the researcher
selects study participants based on the need to ascertain how experts in a field
would react to or judge the phenomena of interest for the study. The researcher
determines what constitutes the expertise needed for the study. For example, a
sample of nurse midwifery educators with expertise in curriculum development
specific to the preparation of nurse midwives could be selected for a study
proposing to determine the effectiveness of two different nurse midwifery
curricula.

25. Diversity sampling
 Diversity sampling, also termed heterogeneity sampling, is a non-probability
sampling procedure used when the investigation requires that subjects with
a wide variety of opinions and views be included in the sample. To achieve
diversity sampling, the researcher would include individuals from all
segments of the population without regard for representation of persons
with these opinions and views as they occur proportionately in the
population.

26. event sampling
 Event sampling in a non-probability sampling procedure in which the
investigator is concerned only with sampling from those specific
occurrences and/ or event that are relevant to the study. For example, the
research student who wrote the proposal” compliance with universal
precaution” would collect her data about nurses using universal precautions
only when they were working with children.

27. Time sampling
 Time sampling is a non-probability sampling procedure used by researchers
who are concerned with collecting data activities that take place at specific
times of the day or night. For example, the researcher who wanted to observe
what was happening during meal time in an intermediate care facility would
collect only at times when meals were being served. Both probability and non-
probability have respected place in research. The important factor in
determining which sampling approach to use is consistency with the research
problem and the purpose of the study.

28. ANY QUESTIONS ?