The document discusses the concept and importance of sampling in research, defining key terms such as population, sample, and types of sampling methods. It categorizes sampling techniques into probability and non-probability methods, detailing various approaches such as simple random sampling, stratified sampling, and convenience sampling among others. The document highlights the advantages and disadvantages of each technique, emphasizing the implications for data quality, bias, and representation of the population.

2. SAMPLING

3. INTRODUCTION
• Sampling is a process of selecting
representative units from an entire population
of a study. Sample is not always possible to
study an entire population; therefore, the
researcher draws a representative part of a
population through sampling process.

4. DEFINITION
• The process of selecting a number of
individuals for a study in such a way that the
individuals represent the larger group from
which they were selected.

6. 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.

7. POPULATION
• The larger group from which individuals are
selected to participate in a study. Population is
the aggregation of all the units in which a
researcher is interested. In other words,
population is the set of people or entire to
which the results of a research are to be
generalized.

8. TYPES OF POPULATION
• Target Population: A target population consist
of the total number of people or objects
which are meeting the designated set of
criteria.
In other words, it is the aggregate of all the
cases with a certain phenomenon about which
the researcher would like to make a
generalization.

9. Continue….
• Accessible population: It is the aggregate of
cases that conform to designated criteria &
are also accessible as subjects for a study.

10. POPULATION TARGET
POPULATION
ACCESSIBLE
POPULATION
SAMPLE
SUBJECTS

11. PURPOSE
• Economical: In most cases, it is not possible &
economical for researchers to study an entire
population. With the help of sampling, the
researcher can save lots of time, money, &
resources to study a phenomenon.

12. Continue….
• Improved quality of data: It is a proven fact that
when a person handles less amount the work of
fewer number of people, then it is easier to
ensure the quality of the outcome.
• 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.

13. Continue….
• 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
cumbersome task.

14. SAMPLING PROCESS
Identifying & defining the target population
Describing the accessible population and ensuring
sampling frame
Specifying the sampling unit
Specifying sample selection methods

15. Determining the sample size
Specifying the sampling plan
Selecting a desired sample

16. FACTORS INFLUENCING SAMPLING
PROCESS
1. Nature of the researcher
Inexperienced investigator
Lack of interest
Lack of honesty
Intensive workload
Inadequate supervision

17. Continue….
2. Nature of the sample
• Inappropriate sampling technique
• equate supervision
• Sample size
• Defective sampling frame

18. Continue….
3. Circumstances
• Lack of time
• Large geographic area
• Lack of cooperation
• Natural calamities

19. TYPES OF SAMPLING TECHNIQUES
• Sampling is the process of selecting a
representative part of the population.
• Sampling techniques are classified in two
broad categories:
 Probability sampling techniques
 Non- Probability sampling techniques

20. TYPES
PROBABILITY
SAMPLING TECHNIQUE
NON- PROBABILITY
SAMPLING TECHNIQUE
Simple Random
Sampling
Stratified random
sampling
Systematic
random sampling
Cluster sampling
Sequential
sampling
 Purposive sampling
Convenience
Sampling
 Consecutive
sampling
 Quota sampling
 Snowball Sampling
 Volunteer sampling

21. PROBABILITY SAMPLING
TECHNIQUE
• It is based on the theory of probability.
• It involve random selection of the
elements/members of the population. In this,
every subject in a population has equal
chance to be selected sampling for a study.
• In probability sampling techniques, the
chances of systematic bias is relatively less
because subjects are randomly selected.

22. 1. Simple random sampling
• This is the most pure & basic probability
sampling design.
• In this type of sampling design, every member
of population has an equal chance of being
selected as subject.
• The entire process of sampling is done in a
single step, with each subject selected
independently of the other members of the
population.

23. Continue….
• The first step of the simple random sampling
technique is to identify the accessible
population & prepare a list of all the
elements/members of the population. The list
of the subjects in population is called as
sampling frame & sample drawn from
sampling frame by using following methods:

24. The lottery
method
The use of table
of random
numbers
The use of
computer

25. The lottery method
• It is most primitive & mechanical method.
• Each member of the population is assigned a
unique number.
• Each number is placed in a bowel or hat & mixed
thoroughly.
• The blind-folded researcher then picks numbered
tags from the hat.
• All the individuals bearing the numbers picked by
the researcher are the subjects for the study.

27. The use of table of random numbers
• This is most commonly & accurately used
method in simple random sampling.
• Random table present several numbers in
rows & columns.
• Researcher initially prepare a numbered list of
the members of the population, & then with a
blindfold chooses a number from the random
table.

28. Continue….
• The same procedure is continued until the
desired number of the subject is achieved.
• If repeatedly similar numbers are
encountered, they are ignored & next
numbers are considered until desired
numbers of the subject are achieved.

30. The use of computer
• Nowadays random tables may be generated
from the computer, & subjects may be
selected as described in the use of random
table.
• For populations with a small number of
members, it is advisable to use the first
method, but if the population has many
members, a computer-aided random selection
is preferred.

31. MERITS
• Ease of assembling the
samples
• Fair way of selecting the
sample
• Require minimum
knowledge about the
population in advance
• It’s an unbiased probability
method
• Free from sampling errors
DEMERITS
• It requires a complete and
up to date list of all the
members of the population
• Does not make use of
knowledge about a
population which
researchers may already
have
• Lot of procedure needs to
be done before sapling
• Expensive and time
consuming

32. 2. Stratified random sampling
• This method is used for heterogeneous
population.
• It is a probability sampling technique wherein
the researcher divides the entire population
into different homogeneous subgroups or
strata, & then randomly selects the final
subjects proportionally from the different
strata.

33. Continue….
• The strata are divided according selected traits
of the population such as age, gender,
religion, socio- economic status, diagnosis,
education, geographical region, type of
institution, type of care, type of registered
nurses, nursing area specialization, site of
care, etc.

35. MERITS
• It represents all groups in
population
• It observes relation
between sub groups
• It observes smallest and
most inaccessible
subgroups in population
• It gives higher statistical
precision
• It saves lot time, money and
efforts
DEMERITS
• It requires accurate
information of the
proportion of
population in each
stratum
• Large population must
be available from which
the sample is being
taken
• Possibility of faulty
classification

36. 3. Systematic random sampling
• Order all units in the sampling frame
• Then every Kth number on the list is selected
K=N/n
N= Number of subjects in target population
n= Size of sample

37. Continue….
 For ex- A researcher wants to choose about
100 subjects from a total target population of
500 people. Therefore, 500/100 = 5.
 Therefore, every 5th person will be selected.

38. MERITS
• It is convenient and
simple to carry out
• Distribution of sample
is spread evenly over
the entire given
population
• It is less cumbersome,
less time consuming
and cheaper
DEMERITS
• If first subject is not
selected randomly it
becomes a non-
random sampling
technique
• Sometimes it results in
biased samples
• If sampling frame is
non- random, this
sampling technique
may not be appropriate
to select a
representative sample

39. 4. Cluster random sampling
• It is defined as a sampling technique in which
the population is divided into already existing
groups (clusters).
• Then a sample of the cluster is selected
randomly from the population.
• This method is used in cases where the
population elements are scattered over a wide
area, & it is impossible to obtain a list of all
the elements.

41. MERITS
• It’s cheap, quick, & easy
for a large population.
• Large population can be
studied and require only
list of the members.
• Investigators to use
existing division such as
district, village/town, etc.
• Same sample can be used
again for study
DEMERITS
• This technique is the
least representative of
the population.
• Possibility of high
sampling error
• This technique is not at
all useful.

42. 5. Sequential Sampling
• This method of sample selection is slightly
different from other methods.
• Here the sample size is not fixed. The
investigator initially selects small sample &
tries out to make inferences; if not able to
draw results, he or she then adds more
subjects until clear-cut inferences can be
drawn.

43. Continue….
 For ex- A researcher is studying association
between smoking & lung cancer. Initially
researcher takes a smallest sample and tries
to drawn inferences.
No. of subject Smokers (A) Nonsmokers (B) Having lung cancer
(A) (B)
20 7 12 2 1
30 18 22 5 3
50 28 22 10 4

44. MERITS
• Facilities to conduct
studies on best
possible smallest
representative
sample
• Helping in
ultimately finding
the interference in
study
DEMERITS
• With this sampling
technique it is not
possible to study a
phenomenon which
needs to be studied
at one point of time
• Requires repeated
enteries into the field
to collect the sample.

45. NON PROBABILITY SAMPLING
TECHNIQUE
• It is a technique wherein the samples are
gathered in a process that does not given 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 non-random
sampling methods.

46. 1. Purposive sampling
• It is more commonly known as ‘judgmental’
sampling’.
• In this type of sampling, subjects are chosen
to be part of the sample with a specific
purpose in mind.
• In purposive sampling, the researcher
believes that some subjects are fit for
research compared to other individual. This is
the reason why they are purposively chosen
as subject.

47. Continue….
• In this sampling technique, samples are
chosen by choice not by chance, through a
judgment made the researcher based on his
or her knowledge about the population

48. MERITS
• Simple to draw sample
& useful in explorative
studies
• Save resources, require
less fieldwork.
DEMERITS
• Require considerable
knowledge about the
population under study.
• It is not always reliable
sample, as conscious biases
may exist.
• Two main weakness of
purposive sampling are with
the authority & in the
sampling process.
• It is usually biased since no
randomization was used to
obtain the sample.

49. 2. Convenience Sampling
• It is probably the most common of all
sampling techniques because it is fast,
inexpensive, easy, & the subject are readily
available.
• It is a non probability sampling technique
where subjects are selected because of their
convenient accessibility & proximity to the
researcher.
• The subjects are selected just because they
are easiest to recruit for the study.
• It is also known as an accidental sampling.

51. MERITS
• This technique is
considered easiest,
cheapest, & least
time consuming.
• This sampling
technique may help
in saving time,
money, & resources.
DEMERITS
• Sampling bias, & the
sample is not
representative of the
entire population.
• It does not provide
the representative
sample from the
population of the
study.

52. 3. Consecutive Sampling
• In this sampling technique, the investigator
pick up all the available subjects who are
meeting the preset inclusion & exclusion
criteria.
• This technique is generally used in small-sized
populations.

53. MERITS
• Little effort for sampling
• It is not expensive, not
time consuming, & not
workforce intensive.
• Ensures more
representativeness of
the selected sample.
DEMERITS
• Researcher has not set
plans about the sample
size & sampling
schedule.
• It always does not
guarantee the selection
of representative
sample.

54. 4. Quota Sampling
• It is non probability sampling technique
wherein the researcher ensures equal or
proportionate representation of subjects,
depending on which trait is considered as the
basis of the quota.
• The bases of the quota are usually age,
gender, education, race, religion, & socio-
economic status.

56. MERITS
• Economically cheap, as
there is no need to
approach all the
candidates.
• Suitable for studies
where the fieldwork has
to be carried out, like
studies related to
market & public opinion
polls.
DEMERITS
• It does not represent all
population
• In the process of sampling
these subgroups, other
traits in the sample may
be overrepresented.
• Not possible to estimate
errors.
• Bias is possible, as
investigator/interviewer
can select persons known
to him.

57. 5. Snowball Sampling
• It is a non probability sampling technique that
is used by researchers to identify potential
subjects in studies where subjects are hard to
locate such as commercial sex workers, drug
abusers, etc.
• This type of sampling technique works like
chain referral. Therefore it is also known as
chain referral sampling.

58. Continue….
• After observing the initial subject, the
researcher asks for assistance from the
subject to help in identify people with a
similar trait of interest.
• The researcher then observes the nominated
subjects & continues in the same way until
obtaining sufficient number of subjects.

60. MERITS
• The chain referral
process allows the
researcher to reach
populations that are
difficult to sample when
using other sampling
methods.
• The process is cheap,
simple, & cost-efficient.
• Need little planning &
lesser workforce
DEMERITS
• Researcher has little
control over the sampling
method.
• Representativeness of the
sample is not guaranteed.
• Sampling bias is also a
fear of researchers when
using this sampling
technique.

61. 6. Volunteer Sampling
• Volunteer sampling is a sampling technique
where participants self-select to become part
of a study because they volunteer when asked,
or respond to an advert.

62. • SAMPLING ERRORS: errors that occur in data
due to the errors inherit in sampling from a
population.

63. • WHEN DOES SAMPLING ERROR OCCURS: it
occurs when researchers takes a random
sample instead of observing every individual
subject that comprises a population. While
dealing with large population this process
becomes the only option, so sampling error is
extremely difficult to avoid