This document discusses various sampling methods used in research. It begins by distinguishing between non-probability and probability sampling. It then provides details on specific non-probability sampling methods like convenience sampling, purposive sampling, snowball sampling, and quota sampling. For probability sampling methods, it explains simple random sampling, probability proportional to size sampling, stratified sampling, cluster sampling, multistage sampling, and systematic sampling. The document aims to help understand different sampling techniques used for primary data collection in research studies.

1. SUBMITTED BY
SUBASH KC
APPLICATION
No:5b4b9345ee5711e9a8cdd3dbc0d2867d
Department of economic studies
Central university of punjab

2. ACKNOWLEDGEMENT
 I would like to express my gratitude to the online
course Acadameic writing because of which I could
prepare this presentation. I also extend my sincere
gratitude to the course coordinator Dr. Ajay semalty
who has given a wonderful lecture on the course

4. Non-probability (Nonrandom)
sampling
Probability (Random) Sampling
Sample is selected without using any
probability techniques
Sample is selected using some
probability techniques.
e.g. Convenience sampling, purposive
(judgement) sampling, Snowball
sampling, Quota sampling
e
e.g. Simple Random Sampling,
Probability proportion to size,
Systematic sampling, Stratified
sampling, cluster sampling, multistage
sampling.

5. Convenience Sampling
 Sample is taken from a group of people easy to
contact or to reach.
 e.g. standing at a mall or a grocery store and asking
people to answer questions.
 Generally, not recommended for research due to
possibility of sampling error and lack of representation
of population.
 But, it can be useful under certain conditions e.g. a
researcher wants to study expenditure of people in
shopping malls during week-ends.

6. Purposive sampling
 Researcher relies on his or her own judgment to draw a
sample from the population.
 It is effective when only limited numbers of people
can serve as primary data sources due to the nature of
research design and aims and objectives.
 E.g. for a research analysing affects of personal tragedy
(such as death of family member) on performance of
senior level managers, the researcher may use his/her
own judgment in order to choose senior level
managers, who could particulate in in-depth
interviews.

7. Snowball Sampling
 It is used where sample for the study to be selected
from the population is rare and scattered in
population.
 After the identification of initial respondent, new
respondents with similar characteristics/traits are
identified through referrals.
 It is often used in hidden populations, such as drug
users, sex workers, locating some diseases among
patients, terrorist affecting families, which are difficult
for researchers to locate/access.

8. Quota Sampling
 The population is first segmented into mutually
exclusive sub-groups (just as in stratified sampling)
 Then judgment/convenience is used to select the
subjects or units from each segment based on a
specified proportion.
 For example, an interviewer may be interested to
sample 200 females and 300 males between the age of
50 and 60. The population will be divided into
exclusive groups (age-wise), then from an age group of
50-60, the sampling will be done through
convenience/judgement.

9. Probability (Random) Sampling

10. Simple Random Sampling (SRS)
 It is a sampling techniques in which every unit in the
population has the same chance of being selected in the
sample.
 In SRS, units from the population are drawn one by one.
 SRS-WR (With replacement): If the unit selected at any
particular draw is replaced back in the population before the
next unit is drawn, it is called as SRS-WR. There is
possibility of one or more population units getting selected
more than once.
 SRS-WOR (Without Replacement): If the sampling
procedure is continued till n distinct units are selected and all
repetitions are ignored, this is called as SRSWOR.

11. Probability Proportional to Size
(PPS)
 In SRS, all units in the population have equal chance
(equal probability) of being selected. However, units
vary in size, so SRS may not be appropriate as SRS does
not take into account size of the unit.
 In PPS, units are selected with probability proportional
to a given measure of size.
 The size measure is the value of an auxiliary variable
(say, x), which is closely related with study variable
(say, y).

12. Stratified Sampling
 In stratified sampling, the population is divided into
subgroups (called as strata) and then sample is
independently drawn from each stratum.
 The strata are constructed in such a way that they are
homogenous with themselves, but have maximum
variability with the strata.
 The strata can be constructed on the basis of
administrative grouping, geographical regions, some other
auxiliary variable.
 Stratified sampling gives better representation to different
cross sections of the population. So, there are little chances
of exclusion of any major group of the population.

13. Cluster Sampling
 It consists of forming suitable clusters of contiguous
population units and surveying all the units in a
sample of clusters.
 It is very useful in many practical surveys, where
listing of population units (from where sample is to be
taken) is not available, but the same may be available
for small segments of the population.
 It is cost saving, but less efficient as compared to other
methods of sampling.

14. Multi-stage Sampling
 The procedure of sampling, which consists of first
selecting the clusters and then randomly choosing a
specified number of units from each selected cluster, is
known as two-stage sampling.
 The clusters that from the units of sampling at first
stage are called as first/primary stage units and the
elements within clusters are known as
second/secondary stage units and so on….

15. Systematic Sampling
 The method in which only the first unit is selected at
random, the rest being automatically selected
according to a pre-determined pattern, is known as
systematic sampling.
 This method is useful in large surveys and where a
sample is selected by field staff themselves.

16. feedback
 This course really helpful for students
 It help to understand what is academic writing

17. THANK YOU