This document discusses different sampling methods and terms. It defines key concepts like population, sample, element, and provides characteristics of a good sample. It outlines advantages and limitations of sampling and categorizes sampling methods into probability and non-probability. Specific probability methods like simple random sampling, stratified sampling, and systematic sampling are described in detail along with their procedures and advantages/disadvantages. Non-probability methods like quota sampling, accidental sampling and judgmental sampling are also briefly introduced.

1. SAMPLING

2. SOME IMPORTANT TERMS.
Population: The aggregate of all units pertaining
to a study is called population
Element: A member of a population is an
element(subject)
Sample: A part of the population is known as the
sample
Sampling: It is the process of drawing sample from
a larger population
Sampling frame: The list of sampling units from
which a sample is taken is called the sampling
frame

3. CHARACTERISTICS OF A GOOD SAMPLE
1. Representativeness: Represent the population
2. Accuracy: Degree to which bias is free from the
sample
3. Precision: Precision is measured by SD and
standard error
4. Adequate sample size ensures reliability

4. ADVANTAGES OF SAMPLING.
1. Reduces time and cost of
research
2. Saves labour
3. Quality of study is often
better
4. Produce quicker results
5. If population is infinite
sampling is only procedure
possible

5. LIMITATIONS OF SAMPLING
Sampling demands a
thorough knowledge of
sampling methods and
procedures.
Complicated sampling
plan requires more
labour.

6. Classification of sampling methods
 Probability sampling
 Non probability sampling

7. PROBABILITY SAMPLING
Probability sampling are those that clearly specify the
probability or likelihood of inclusion of each element
or individual in the sample .

8. CONDITIONS OF PROBABILITY
SAMPLING
The size of the parent population must be known to
the investigator.
Each element in the population must have equal
chance of being included in subsequent sample.
The desired sample size must be clearly specified.

9. Positive&negative points…
Positive point :-The obtained samples are considered
representative.
Negative point : Certain amount of sampling error
exists because there is a limited amount of the entire
population.

10. Types of probability sampling…
Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
Area sampling
Multi-stage sampling
Multi phase sampling
Sampling with probability proportionate to size
Replicated sampling

11. Simple random sampling
A simple random sample selected from a population
in such a way that every member of the population
has equal chance of being selected and selection of
any individual does not influence the selection of any
other
Random sample is a sample selected at random.
Sample selection should be done in such a way that
any bias on the part of the observer shall be avoided

12. PROCEDURE
Enumeration of all elements in the population
Preparation of a list of all elements
Drawing sample numbers by using lottery method,
tables of random numbers or a computer

13. Two methods for random sampling
Lottery method
Table of random numbers

14. LOTTERY METHOD
All items of the universe are numbered or named on
separates lips of paper of identical size and shape
Slips are then folded
Mixed in a container
A blind fold selection
Number of slips taken =desired sample size

15. TABLE OF RANDOM NUMBERS
Several standard tables of standard tables of random
numbers are available
E.g.: Tippet’s table, Fisher’s table, Kendall’s table,
Rao’s etc
These tables are known as random sampling
numbers
Tables are used for getting random numbers
corresponding to which we select from population

16. ADVANTAGES
All elements in the population
have an equal chance of being
selected
Easiest to study
Most simple type of probability
sample
Does not require prior knowledge
The amount of sampling error can
be early computed

17. Disadvantages
It is impractical because of non availability of
population list
If the size of the sample selected is small ,the results
may not be reliable
A simple random design may be expensive in time
and money
The size of the sample required to ensure its
representativeness is usually larger under this type of
study

18. Sampling error in this sampling is greater than other
probability samples
This technique does not ensure proportionate
representations to various groups consulting the
population
The use of simple random sampling may be wasteful
because we fail to use all the known informations
about the population

19. Stratified random sampling
In stratified random sampling ,we must devide the
population into different subgroups known as strata
Items in each stratum are homogeneous
From each strata items are selected by simple random
sample method
This method has the advantage of a simple random
sampling method
Different groups in the population get
representations
It ensures greater accuracy

20. It is appropriate for large heterogeneous population
Stratification ensures representation to all relevant
subgroups
Provides data for analyzing various subgroups.

21. Division of stratified sampling
 1.proportionate stratified sampling
2. dispropotionate stratified sampling

22. Propotionate stratified sampling ..
In propotionate stratified sampling ,number of items
selected from each sample is propotional to size of
each stratum
Number of items taken from each stratum is on the
basis of size of each stratum
( eg)

23. Advantages
It enhances representativeness of the sample
It gives higher statistical efficiency
It is easy to carry out

24. Disadvantages
A prior knowledge of the composition of the
population is required
This method is very expensive in money &time
Identification of strata might lead to classification
errors

25. Disproportionate stratified
sampling
Dispropotionate stratified random sampling where
equal number of items is selected from each
stratum ,irrespective of size

26. Advantages
It is less time consuming
It facilitates giving appropriate weightage to
particular groups which are small but important

27. Disadvantages
The sample may be less representative
This method requires prior knowledge

28. Systematic sampling
This method of sampling is an alternative to random
sampling
It consist of taking K th (or N th)item in the
population after a random start with an item from 1
to K
as the interval between sample units are fixed ,this
method is also called fixed interval method

29. Advantages
It is much simpler than random sampling
It is easy to instruct the field investigations
The method requires less time
This method is cheaper than simple random sampling
Easier to check whether every K th has been included
in the sample
Sample is spread evenly over the population
It is statistically more efficient than simple random
sampling

30. Disadvantage
This method ignores all element between two K th
elements selected
As each element does not have equal chances of
being selected ,the resulting sample is not a random
one
This method may sometimes gives a biased sample

31. Cluster sampling
When population are scattered over a wider area
and a list of population element is not readily
available.
Cluster sampling means random selection of
sampling units consisting of population elements
Cluster sampling - the subjects are selected in
groups or clusters rather than randomly

32. Cluster sampling process
Identify clusters
Examine the nature of clusters
Determine the number of stages

33. Advantages
The method is much easier and more convenient to
apply when large populations are studied or large
geographic areas are covered
The cost of this method is much less
This method promotes convenience of field work
Sampling does not require more time
This method is flexible

34. Disadvantages
The cluster may vary and this variation could increase
the bias of the resulting sample
The sampling error in this method of sampling is
greater

35. Area sampling ..
This is an important form of cluster sampling
As the geographic areas are selected as sampling units
in such cases their sampling is called area sampling
Area sampling invariably involves multistage
sampling and sub sampling
Eg…

36. Multi stage sampling
In this sampling is carried out in two or more stages
The population is regarded as being composed of a
number of first stage sampling unit
First a sample of the first stage sampling unit is
drawn
From each first stage sampling units a sample of the
second stage sampling units is drawn
The procedures comes down to the final sampling
units
Appropriate random sampling method is adopted at
each stage

37. Advantages
It results in concentration of field work in compact
small areas and consequently in saving time ,labour
and money
It is convenient ,efficient, and flexible than single
stage sampling.

38. Disadvantages
The procedure of estimating sampling error is
complicated

39. Sampling with probability proportional
size(PPS)
If one primary cluster has twice as large population as
another ,it is given twice the chance of being selected
The PPS is a better method for getting a
representative sample of population element in
multistage sampling
Not all clusters are the same size.
Can weigh the clusters to equate the difference.
Can weigh the chances of a cluster being selected

40. Advantages
Clusters of various size gets proportionate
representation
PPS leads to great precision and a constant sampling
fraction at the second stage

41. Limitation
PPS cannot be used when the sizes of the primary
sampling clusters are not known

42. Application
Used in all multi stage sampling

43. Multi-phase sampling
Multi phase sampling is different from multi stage
sampling
In multi phase sampling the different phases of
observation relate to sample units of the same type

44. Replicated sample
Replicated sampling involves selection of a certain
number of sub samples rather than one full sample
in a population

45. Advantages
It provides simple means of calculating the sampling
errors
Its is practical

46. Dis advantages
A disadvantage of replicated sampling is that its
limits the amount of stratification that can be
employed

48. II NON PROBABILITY SAMPLING

49. Non probability sampling
Non probability sampling is one in which there is no
way of assessing the probability of the element or
group elements ,of population being included in the
sample .

50. Important sampling methods..
Quota sampling
Accidental sampling
Judgmental sampling
Snowball sampling
 purposive or deliberate
Convenience sampling
Self selection sampling

51. Quota sampling
Quota sampling - quotas for certain types of
people or organizations are selected as the sample
Interviewers are required to find cases with particular
characteristics
E.g., certain number of teenagers, etc.
Advantage– better than convenience; introduce
some diversity
disadvantage –
It is nonrandom sampling

52. Accidental sampling
Accidental sampling is a type of
nonprobability sampling which involves the sample
being drawn from that part of the population which is
close to hand. That is, a sample population selected
because it is readily available and convenient

53. The researcher using such a sample cannot
scientifically make generalizations about the total
population from this sample because it would not be
representative enough
This type of sampling is most useful for pilot testing
Eg (shoping complex)

54. Judgemental sampling
In judgement sampling, the researcher or some other
"expert" uses his/her judgement in selecting the units
from the population for study based on the
population’s parameters.

55. Snow ball sampling
Snowball sampling – an individual or group of individuals
are sampled. They provide other sources to be sampled.
Sampling snowballs into a large selection.
Useful for hard to identify groups.
E.g., study of criminal organizations
May lead to biased sample
Sociogram – a map of individuals and their references.

57. Purposive sampling
Purposive sampling is the selection of items in
accordance with some purposive principle the items
are selected in accordance with that criterion

58. Convenience sampling method
In this method investigator is the most important
person
The whole sample is picked up according to his
convenience
He decided what should or should not be included in
the sample
It is to be seen as to what is the availability
,accessibility as well as the command of the
investigator

59. Sample is not picked up with the help of any scientific
method.
There is no preplanning for the preparation of a
sample
Obviously in research this method is quite
undependable

60. Self-selection sampling
Self-selection sampling – test yourself
Often used in sensation/perception experiments
Problems
Lacks diversity
Can be extremely biased