Probability and non-probability sampling were discussed. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling aim to give all population members an equal chance of selection. Non-probability methods like convenience sampling, judgmental sampling, and snowball sampling rely on accessibility and do not aim for equal selection probability. While probability sampling is preferred for generating data about a whole population, non-probability techniques are commonly used in business research due to greater respondent cooperation.

1. PRESENTED BY:
IMPANA U S
1ST M.COM
Under the guidance of
Sundar B. N.
Asst. Prof. & Course Co-ordinator
GFGCW, PG Studies in Commerce
Holenarasipura

2. CONTENTS
Introduction
Meaning
Types
Conclusion
Bibliography

3.  Statistical agencies prefer the probability random
sampling. In business, companies, marketers mostly
relay on non-probability sampling for their research,
the researcher prefers that because of getting
confidence cooperation from his respondent
especially in the business sample survey like
consumer price index.

4. Meaning
A sample is a subset of individuals from a larger
population. Sampling means selecting the group that
you will actually collect data from in your research.
For example, if you are researching the opinions of
students in your university, you could survey a
sample of 100 students.
In statistics, sampling allows you to test a hypothesis
about the characteristics of a population.

5. Type of Sampling
1. Probability Sampling:-Probability sampling is
known as ‘random sampling’ this is a sampling which
permits every single item from the universe to have an equal
chance of presence in the sample. For instance in a raffle draw
were individual units will be picked from the over all group
not a deliberately nonetheless by certain process, this incident
is only a blind of chance that will limits whether unique items
are the additional items is to be preferred
2. Non-probability Sampling :
Non probability sample a particular member of the population
being chosen is unknown.
In Probability sampling, randomness is the element of control.
In Non-probability sampling, it relies on personal judgment .

6. Probability Sampling
•Population divided
into clusters, random
sample of cluster is
selected from as
simple random
design
•Population is
divide
•Into sub-
population/stratu
m and subjects
selected randomly
•Every nth element
chosen started at
random and
picking every n’th
element in
succession
• All elements are
considered and
each has equal
chance of being
selected
Simple
Random
sampling
Systematic
sampling
C l u s t e r
sampling
Stratified
sampling

7. Probability sampling
1. Simple Random Sampling: here all member have
the same chance(probability) of being selected.
Random method provides an unbiased cross
selection of the population.
For example,
we wish to draw a sample of 50 students from a
population of 400 students. Place all 400 names in a
container and draw out 50 names one by one.

8. 2.Systematic sampling :- Each member
of the sample comes after an equal interval from its
previous member
for example, for a sample of 50 students, the
sampling fraction is 50/400: 1/8 i.e. select one student
out of every eight students in the population. The
starting points for the selection is chosen at random.
start
Houses to survey

9. 3. Stratified Sampling: The population is
divided into smaller homogenous group or strata by some
characteristic and from each of these strata members are
selected randomly.
Finally from each stratum using simple random or
systematic sample method is used to select final sample.
Total population
Population divided
into strata Stratified sample

10. 4.Cluster sampling(Area
sampling)
A researcher/enumerator selects sampling units at
random and then does complete observation of all
units in the group
For example, the study involves primary schools.
Select randomly 15 schools . Then study all the children
of 15 schools . in cluster sampling the unit of
sampling consists of multiple cases. It is also know as
area sampling . as the selection of individuals member
is made on the basis of place residence or employment

11. Non probability sampling
• Referred by
current
sample
elements
•Relevant
characteristics are
used to segregate the
sample to improve
its
representativeness
• Deliberately
selected
sample to
conform to
some criteria
• Based on
ease of
accessibility
Convenience
sampling
Judgmental
sampling
Snowball
sampling
Quota
sampling

12. Non probability sampling
1. Purposive sampling : In this sampling
method, the researcher selects a “typically group” of
individuals who might represent the larger
population and then collects data from this group.
also know as judgmental sampling.
Purposive sample

13. 2. Convenience sampling : It refers to the
procedures of obtaining units or members who are
most conveniently available. It consists of units
which are obtained because cases are readily
available.
In selecting the incidental sample, the researcher
determines the required sample size and then
simply collects data on that number of individuals
who available easily.
Researcher
No black figures in
sample
Convenienc
e sample

14. 3. Quote Sampling : The selection of the sample is
made by the researcher, who decides the quotas for selecting
sample from specified sub group of the population.
For example, an interviewer might be need data from 40
adults and 20 adolescents in order to study students’
television viewing habits.
Selection will be
20 adult men and 20 adult women
10 adolescent girls and 10 adolescent boys

15. 4. Snowball sampling:
In snowball sampling, the researcher Identifying
and selecting available respondent who meet the criteria
for inclusion.
After the data have been collected from the subject, the
researcher asks for a referral of other individuals, who
would also meet the criteria and represent the population of
concern.

16. Conclusion
In conclusion the probability random sampling in
more preferable because the researcher generate his
data for the use of entire population by using
probabilistic method to control biased during the
sampling , based on evidence generated by the
agencies of statistical official that the non-probability
techniques is based on purpose that lead to
assumption which resulting to risk. Basing on
assumption means one will generate inappropriate
generalization of the population

17. Bibliography
Sampling meaning and Types(Retrieved from,
https://www.slideshare.net.)Date:-22/4/2021)
Sampling meaning and types(Retrieved from
Dohert M. probability versus Non probability
sampling in sample surveys. The new zealand
statistical review.1994.p.77-100.)