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SAMPLING
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The Sampling Design Process
Define the Population
Determine the Sampling Frame
Select Sampling Technique(s)
Determine the Sample Size
Execute the Sampling Process
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Population
The target population is the collection of elements or objectsthat possess the information sought by the researcher and
about which inferences are to be made. The target
population should be defined in terms of elements, sampling
units, extent, and time.
An element is the object about which or from which the
information is desired, e.g., the respondent.
A sampling unit is an element, or a unit containing the
element, that is available for selection at some stage of thesampling process.
Extent refers to the geographical boundaries.
Time is the time period under consideration.
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Sample
Sampling
Process of separating the representative part from populationis known as sampling. The method of selecting a specified
portion, called a sample, from a population, from which
information concerning the whole can be inferred.
A portion of the population that represents population
characteristics is called as sample. They are the subset
of the population that should represent the entire
population. They have similar characteristics ofpopulation
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Population Size: Total number of elements in population
Element:Individual member of population
Sample:Representative part of the population
Sample frame:A list of elements from which the sample isactually drawn
Sample Size: Total number of elements selected frompopulation.Subject:Individual member of sample
Respondent: Who answers the query.
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Categorization of Sampling method
There are two categories of sampling method.
Probability based:
All those sampling methods in which each and every
member of the population gets an equal chance to becomethe part of the sample.
Non probability based:
In non-probability based sampling methods each and everymember from the population does not get an equal chance
of being selected in the sample.
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Sampling
Probability
Simple Random stratifiedcluster
nonsystematic
Proportionatesystematic
Disproportionate
size variance
Non Probability
quota
snowball
judgment
convenience
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Probability based sampling methods
Sampling procedure in which each and
every element of population has a fixedprobabilistic chance of being selected
for the sample.
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Probability
Simple Random stratifiedcluster
nonsystematic
Proportionatesystematic
Disproportionate
size variance
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Simplerandom Sampling Method
With simple random sampling, the
probability of selection into the sample
is known and equal for all members
of population. Sample is selected in sucha way that every element of the
population has a known and equal
chance of being chosen for the sample.
Also called random sample. The sampleis selected from the entire population i.e.
without dividing respondents into
groups.
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Systematic:
A probability sampling technique in which the sample is chosen
by selecting a random starting point and then picking every nth
element in succession from the sampling frame.Eg: pick 3, Then 6 ,9,12,15,18
Nonsystematic:
This implies that every number is selected independently of
every other element. This method is equivalent to a lottery
system.
Eg: A lucky draw.
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Stratified Sampling Method
A probability sampling technique that uses two step
process to partition into subpopulation, or strata .
samples are selected from each stratum by a
random procedure.Probability samples that force sample to be more
representative of the population. It is obtained by
dividing the population into groups called strata,
then simple random samples are taken from each of
the strata. It can be done in two ways:
Proportionate & Disproportionate.
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Proportionate: (Based on relationship)
Size:Group size matters a lot.The bigger
the size of the strata the more you
select, the smaller the size of strata
the less you select.
Variance:
It depends on the differences thatexists in a group. More the difference
more you select, the less the
difference less you select.
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Steps Involved in Stratified Sampling
1. Divide the population into stratas or groups.2. Identify the population in each strata.3. Select the number of respondents either
proportionately or disproportionately.4. Select final respondents by applying simplerandom sampling method
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Total Population
Male
Female
60 students
10%
40 students
10%
100 students: 10%
6
4
10
Selecting Numbers of Respondents by Proportionate
Proportionate ( Size )
Larger the size of the group the more we select, the smaller
the size of strata the less we select.
Strata-1
Strata-2
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Selecting Numbers of Respondents by Proportionate
Proportionate ( Variance )
More the difference in a group more we select the less the
differences in a group the less we select.
Total Population
Male
Female
60 students
40 students
100 students3
6
d
dd
Here the differences in strata-2 are more than strata-1 and the
relationship is 1:2 so for every one respondent from strata-1
well select two respondents from strata-2 untill the desired
sample size is achieved
Strata-1
Strata-2
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Disproportionate
It is the sampling done without any
relationship. Here importance formula is used
because the strata size doesnt reflect the
relative proportions of the population. It
depends on the own judgment of the
researcher about the importance of each of the
strata for the research. You choose the desiredsample size according to your judgment
about the importance of the strata in the
research.
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Total Population
Male
Female
60 students
40 students
100 students
In this type the Respondent are selected on the Judgment
of the Researcher. Researcher decide which group is more
important
5
5
Here the researcher thinks that both the strata
are equally important for the research.
Strata-1
Strata-2
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Cluster Sampling Method
Population is divided into internally heterogeneoussubgroups. Some are randomly selected for further
study.
Advantages:Lowest cost per sample especially with
geographical clusters.
Easy to do without a population list.
Disadvantages:
Often lower statistical efficiency ( more error) due to
subgroups being homogenous rather than being
heterogeneous.
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Cluster ( Area Sampling Method )DHA
DHA
Phase 1
DHA
Phase 2
DHA
Phase 3
DHA
Phase 4
Street 1 Street 2 Street 1 Street 2 Street 1 Street 2 Street 1 Street 2
Khayaban Khayaban Khayaban Khayaban
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Non probability based Sampling
methods
In non-probability based sampling
methods each and every member fromthe population does not get the equal
chance of being selected in the sample.
It rely on the personal judgment orconvenience of the researcher.
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Convenience
Convenience samples are sample drawn at the convenience of
the researcher. According to most convenient location, time,
etc respondents are selected. Convenience sampling may
misrepresent the population.
A sampling procedure that leaves the selection of respondentstotally to the field researcher, with no quotas or qualifications
imposed. It consists of those units of the population that are
easily accessible.
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Judgment
Judgement sampling is a form of non-
probability sampling in which thepopulation elements are selected based
on the judgment of the researcher.
In judgment sampling researcher useshis/ her own educated guess or
judgment to identify who will be in
the sample.
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Snow ball
Snowball sampling is commonly used when it is difficult to
identify members of the desired population.Make contact
with one or two respondents in the population.Ask these
new respondents to identify further new respondents andso on. And this process of obtaining data by initial respondent
,and then from referral to referral is called as snow ball.
E.g: Giving the questionnaire to the students who know other
students of their batch and then asking them to identify other
student whom they know.
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Quota
The quota sample establishes a specific
quota or percentage for various types of
individuals to be interviewed.
The size of the quota are determined by the
researchers belief for relative size of each
class of respondent in the population. Often,
quota sampling is used as means of
ensuring convenience sample size
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Quota sampling may be viewed as two-stage restricted
judgmental sampling.
The first stage consists of developing control categories,or quotas, of population elements.
In the second stage, sample elements are selected
based on convenience or judgment.
Population Sample
composition composition
Control
Characteristic Percentage Percentage Number
SexMale 48 48 480
Female 52 52 520
____ ____ ____
100 100 1000
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Strength and weakness of sampling techniques
Convenience
Sampling
Judgmental
Sampling
Quota
sampling
Snow Ball
sampling
strength weakness
Least expensive, least time
consuming, most convenient
Selection biasness, sample is
not representative of (P)
Low cost, convenient , less
time consuming
Doesnt allow generalization,
subjective instead of objective
Sample can be controlled
from certain characteristics.
Selection bias, no assurance
of representative.
Can estimate rare
characteristics
Time consuming
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Strength and weakness of sampling techniquesStrength Weakness
Easily understood,results are
projectable
Difficult to construct sampling
frame, expensive, lower
precision, no assurance of
representative
Can increase representativeness, easier to implement, than
Srs, Sampling frame not
necessary.
Can decrease representative
Includes all important
subpopulation, precision.
Difficult to select relevant
stratification variable,expensive,not feasible to
verify many variables.
Cost effective ,
easy implement
Low statistical efficiency
Simple
Random
Systematic
sampling
Stratified
sampling
Cluster
sampling
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Sample vs. Census
Conditions Favoring the Use of
Type of Study Sample Census
1. Budget Small Large
2. Time available Short Long
3. Population size Large Small
4. Variance in the characteristic Small Large
5. Cost of sampling errors Low High
6. Cost of nonsampling errors High Low
7. Nature of measurement Destructive Nondestructive
8. Attention to individual cases Yes No
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Factors to determine sample size
1. Cost2. Time
3. Importance of decision4. Reliability requirements5. Population size6. Nature of the problem
7. Diversity of population
S l Si U d i R h
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Sample Sizes Used in Research
Studies
Type of Study Minimum Size Typical Range
Problem identification research
(e.g. market potential)
500 1,000-2,500
Problem-solving research (e.g.pricing)
200 300-500
Product tests 200 300-500
Test marketing studies 200 300-500
TV, radio, or print advertising (percommercial or ad tested)
150 200-300
Test-market audits 10 stores 10-20 stores
Focus groups 2 groups 4-12 groups
T
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