Download Sampling Techniques - GVM COLLEGE OF EDUCATION

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When every unit of the population is examined.
This is known as Census method.
On the other hand when a small group selected
as representatives of the population is
examined. ___ It is known as Sampling method
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Sampling is a process of inferring something
about a large group of elements by studying
only a part of it
OR
It is a process of selecting relatively a small
group of people representing the population.
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It is a miniature / replica of the entire group
from which it has been selected
It is selected part which is used to ascertain
the characteristics of the large group.
It is small/ cross section of larger whole
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The larger whole from which the sample has
been taken is known as population.
It may consists of persons, objects,
attributes, qualities, animals etc who have
atleast one common characteristic ,for example
all graduates.
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The measures of samples are known as
statistics.
The measures of population are known as
parameters.
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Technically ,sample is drawn from Sampling
Frame i.e. a complete, accurate and up-to-date
list of all the units in the population.
This frame is either constructed by the
researcher for the purpose of his study
OR
may use some existing list of frame
(Telephone Directories ,List of schools/colleges
in a state)
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The basic requirements of a scientific or
‘good’ sample are:
1)
Representativeness
2)
Adequate and,
3)
Accurate
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A representative sample is one which is miniature or replica
ideally in all respects of the population from which it is
withdrawn.
For this population needs to defined properly i.e. whether it is
finite or infinite.
So that there remains no ambiguity as to whether a given unit
belongs to the population or not.
An adequate sample is one which have enough cases to ensure
reliable results.
It means ,adequate is related with size of sample
Size of the sample will depend upon the nature
of the population .
So the size of the sample is determined on the
basis of
1)
Variability in the population
2)
3)
The degree of precision required
The level of confidence at which the results
are to be required.
Sampling
Methods
Probability
Sampling
Non-Probability
Sampling
Probability Sampling
•Each unit of the
population has equal
chance of being
included in the sample.
Non Probability Sampling
•Statistical theory is
applicable.
•Neither each unit
has equal chance nor
the chance of its
being included in the
sample are known.
•It is not possible in
this
•It leads to
representative and
adequate sample
•It is left to the
chance or luck.
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Probability sampling is technique where units
/elements of population are not selected at the
discretion of the researcher rather by means
of certain procedures which ensure that every
unit of a population has one fixed probability
chance of being included in the sample.
Simple
random
sampling
Cluster
sampling
Probability
sampling
Systematic
sampling
Stratified
random
sampling
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It is method of selecting a sample from a finite population.
Random sample is selected in such a way that every unit of the
population has an equal and independent chance of being
included.
Define the population
Listing of the population
Deciding the size of the sample
Selection of the sample by use of a) Lottery method b) Table of
random numbers.
Listing
Population
From 1 to N
Defining
Population
Random
Sampling
Steps
Selection of
Sample
Deciding
Size of
Sample
A random sample thus selected will have the
following points to its credits :
i.
There will be no consistent bias.
ii.
On the average the sample will be
representatives.
iii. The degree of discrepancy can be calculated
by using appropriate SE formula which is
applicable to random sample.
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1)
2)
3)
4)
It involves the listing of the population units in
a systematic manner.
Steps:
Listing of the units of population in some order –either
alphabetically/ seniority wise etc
Determined the Sampling Fraction and also the number of Kth unit
i.e. K = N/n.
Choose a random number between 1 to K, both inclusive,
Select every Kth unit from the list.
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1)
2)
3)
4)
5)
It is useful when the units in the population are not available.
In this stratification of the Main Population is done into a number of
sub-population on the basis of some stratification criteria each of
which is homogeneous w.r.t. one or more characteristics
Steps:
Decide upon the relevant stratification criteria.___ It may be sex,
age, SES, Geographical region etc
Divide the entire population into sub population based on
Stratification Criteria.
List up the units separately in each sub- population
Select the requisite number of units from each sub – population by
using random technique.
All the sub- samples representing sub- population make the main
sample
It is used when the population is infinite, where a list
of units of population does not exist, where the
geographic distribution is scattered and when
sampling of individual units is not convenient for
administrative reasons
Steps:
1) It involves division of population of elementary units
into groups/clusters that serve as primary sampling
units
2) Selection of clusters is then made up to make the
sample instead of individual member because here
cluster is the sampling unit.
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It is used in large scale survey where the
researcher has to select a sample a 2, 3, 4
stages.
For example in Survey type studies at the
National level.
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Simple Random Sampling is used when the population is finite.
Stratified Sampling is used when list of units of individual in a
population are not available.
Cluster Sampling is used when the population under study is
infinite.
Multistage Sampling is used in large scale service for a more
comprehensive investigation.
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In this sampling the units of sampling are
selected at the discretion of the researcher.
Guiding Factors in the Non-probability Sampling
are
a) Convenience of the researcher
b) Experience of the researcher
c)
Availability of the subjects
Incidental
NonProbability
Sampling
Quota
Purposive
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It is generally used with those groups which are
selected because of the easy availability of the
sampling units.
It is based on the assumption that a good researcher
has a good judgment.
A quota sample involves the selection of the sample
units within each stratum or quotas on the basis of
the judgment of the researcher rather than on
calculable chance of being included in it.