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.
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.
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)
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
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
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.
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
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
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 .
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.
56.
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
