Non-probability sampling methods allow researchers to select sample subjects without assigning probabilities, which can lead to findings that are not generalizable to the population. These methods include convenience sampling, quota sampling, judgment sampling, and network sampling, each with their own advantages and disadvantages, often used for qualitative research or when time and budget are constraints. While effective for quick data collection, non-probability sampling may introduce bias and lack representation of the entire population.

2. In non-probability sampling designs, the elements in the population
do not have any probabilities attached to their being chosen as
sample subjects.
This means that the findings from the study of the sample cannot
be confidently generalized to the population.
As stated earlier, however, researchers may at times be less concerned
about generalisability than obtaining some preliminary information i
n a quick and inexpensive way.
They would then resort to non-probability sampling. Sometimes
non-probability sampling could be the only way to obtain data.
The non-probability sampling designs, which fit into the broad categ
ories of convenience sampling and purposive sampling.

3. • An example of convenience sampling would be using student volu
nteers known to the researcher. Researchers can send the survey to
students belonging to a particular school, college, or university, an
d act as a sample.
• In an organization, for studying the career goals of 500 employees,
technically, the sample selected should have proportionate number
s of males and females. Which means there should be 250 males a
nd 250 females. Since this is unlikely, the researcher selects the gro
ups or strata using quota sampling.
• Researchers also use this type of sampling to conduct research inv
olving a particular illness in patients or a rare disease. Researchers
can seek help from subjects to refer to other subjects suffering fro
m the same ailment to form a subjective sample to carry out the
study.

4. • Use this type of sampling to indicate if a particular trait or
characteristic exists in a population.
• Researchers widely use the non-probability sampling method
when they aim at conducting qualitative research, pilot studie
s, or exploratory research.
• Researchers use it when they have limited time to conduct r
esearch or have budget constraints.
• When the researcher needs to observe whether a particular
issue needs in-depth analysis, he applies this method.
• Use it when you do not intend to generate results that will
generalize the entire population.

5. • Probability Sampling methods give a very small space for judgment. A pers
on with sound knowledge and ability on the subject matter can best perfor
m if the person is permitted to conduct non-probability sampling.
• This saves time and money both at the same time by reducing the adminis
trative hassles and travelling etc.
• This system fits best when the exhaustive population is not defined.
• Non-probability sampling techniques are a more conducive and practical m
ethod for researchers deploying surveys in the real world.
• Getting responses using non-probability sampling is faster and more cost-e
ffective than probability sampling because the sample is known to the res
earcher.
• Effective when it is unfeasible or impractical to conduct probability samplin
g.

6. • Excessive dependency on judgment
• Needs much purpose-oriented pollsters
• Focuses on simplicity over effectiveness
• Lack of representation of the entire population
• Lower level of generalisation of research findings

8. Also called as haphazard or accidental sampling. It refers to sampling by obtainin
g units or people who are most conveniently available.
For example, it may be convenient and economical to sample employers in comp
anies in a nearby area, sample from a pool of friends and neighbours.
The person on the street interview conducted by TV programs is another example
TV interviewers go on the street with camera and microphone to talk to few peo
ple who are convenient to interview.
The people walking past a TV studio in the middle of the day do not represent
everyone (Homemaker, People in the rural areas likewise).
TV interviewers select people who look normal to them and avoid who are unattr
active, poor, very old etc.
Convenience samples are least reliable but normally the cheapest and easiest to
conduct

10. • When the universe is not clearly defined
• Where sampling unit is not clear and
• When a complete source list is not available.

11. ➢ Collect data quickly
➢ Inexpensive methodology
➢ Easy to do research
➢ Fewer rules to follow
➢ Readily available sample
➢ Low cost
➢ High vulnerable to selectio
n bias
➢ Generalisability is unclear
➢ High level of sampling err
or

12. Quota sampling combines the features of purposive
sampling and stratified sampling.
The population is first divided into mutually exclusiv
e sub-groups as in stratified sampling
In this researchers create a sample involving individ
uals(choose according to specific traits or qualitie
s) that represent a population
Under quota sampling, the field workers include onl
y those units which conform to certain specified
parameters/proportions in the sample.

14. In this case the researcher first identifies relevant c
ategories of people (Ex; Male & Female, or Unde
r age of 30, age 30 to 60, over 60 etc.) then deci
de how many to get in each category.
The researcher decides to select 5 males and 5 fe
males under age 30, 10 males and 10 females a
ged 30 to 60 and 5 males and 5 females over th
e age of 60 for a 40 person sample.
Thus the number of people in various categories o
f sample is fixed

15. 1. Quota sampling ensures convenience in executin
g sampling study.
2. When the respondent refuses to cooperate, he
may be replaced by another person who is read
y to furnish information
3. Quota sampling is less expensive and speedy
4. When the population has no suitable frame, quo
ta sampling is the only practical method.
5. Collection of data through quota sampling meth
od is not a time consuming one.

16. 1. The interviewer interviews people who are easily avail
able and accessible. So, the possibility of collecting va
luable data is affected in Quota sampling.
2. Bias arises in the matter of selection of sample units.
3. The work of the interviewer cannot be supervised pro
perly. So, there is no certainty of correctness of data.
4. Quota sampling method requires several investigators
. Each one cannot be equally competent. So, the resul
ts derived from the study may not be uniform.

17. Depending upon the type of topic, the researcher lays down the criteria
for the subjects to be included in the sample. Whoever meets that crit
eria could be selected in the sample.
The researcher might select such cases or might provide the criteria to
somebody else and leave it to his/her judgement for the actual selecti
on of the subjects i.e. Such a sample is also called as Judgement/Pur
posive/Expert Opinion sampling.
Judgement sampling involves the selection of a group from the populati
on on the basis of available information.
It is the selection of the group by intuition on the basis of criteria deeme
d to be self evident.
Under this method, units are included in the sample on the basis of the
judgement that the units possess the required characteristics to qualif
y as representatives of the population.

19. A researcher is interested in studying students who are enrolled in
a course on Research Methods, are highly regular, are frequent
participants in the class discussion and often come with new id
eas.
The criteria has been laid down, the researcher may do this job hi
mself or may ask the teacher of the class to select the students
by using the said criteria.
In the latter situation we are leaving it to the judgement of the te
acher to select the subjects.
Similarly we can give same criteria to the fieldworkers and leave it
to their judgement to select the subjects accordingly

20. Judgement Sampling
Disadvantages
1. There is uncontrolled variability and
bias in the estimates in Judgement
sampling
2. The success of Judgement sampling
method is solely dependent on a th
orough knowledge of the populatio
n and elimination of the use of infe
rential parametric statistical tools fo
r the purpose of generalization.
3. Complete reliance on intuition and
hunch is risky in Judgement sampli
ng.
Advantages
• Judgement sampling elimin
ates 5e cost and time in pr
eparing the sample
• Judgement sampling meth
od enables the researcher t
o include the positive aspe
cts of stratification in the s
ample.

21. Also called as Network/Chain/Referral/Reputational sampling.
It is a method of identifying and sampling(selecting) cases in the n
etwork.
It is based on an analogy to a snowball, which begins small but be
comes larger as it is rolled on wet snow and picks up additional
snow.
It begins with one or a few people or cases and spreads out on the
basis of links to thee initial cases.
This design has been found quite useful where respondents are diff
icult to identify and are best located through referral networks.
The group is used to locate others who possess similar characteristi
cs and who in turn identify others

22. A researcher examines friendship networks among teena
gers in a community.
He/she begins with 3 teenagers who do not know each
other.
Each teen names 4 close friends. The researcher then go
es to the 4 friends and asks each to name 4 close frie
nds, then goes to the those 4 and dose the same thin
g again and so forth.
The researcher eventually stops either because of no ne
w names are given indicating a closed network or bec
ause the network is so large that it is at thee limit of
what he/she can study

24. Difference Between Non-Probability Samplin
g and Probability Sampling
Non-probability sampling
• Sample selection based on the su
bjective judgment of the research
er.
• Not everyone has an equal chanc
e to participate.
• The researcher does not consider
sampling bias.
• Useful when the population has si
milar traits.
• The sample does not accurately r
epresent the population.
• Finding respondents is easy.
Probability sampling
• The sample is selected at random.
• Everyone in the population has an
equal chance of getting selected.
• Used when sampling bias has to b
e reduced.
• Useful when the population is dive
rse.
• Used to create an accurate sample.
• Finding the right respondents is no
t easy.

25. Reference
• Advantages and Disadvantages of Non-Probabilit
y Sampling. Retrieved from. https://www.mathsto
pia.net/sampling/non-probability-sampling
• https://accountlearning.com/non-probability-sam
pling-methods-advantages-disadvantages/
• https://www.questionpro.com/blog/non-probabili
ty-sampling/
• Kothari, C. R. (2004). Research methodology: Met
hods and techniques. New Age International.