Post on 22-Jan-2018
Introduction
Basis of Sampling
Sampling Techniques
Probability based samples
Non-probability based or purposive samples
Planning a sample survey
Summary
Context Of Presentation
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A. Reliability
Which measurement is repeatable and consistentI. Precision
o Free from random errorII. Sensitivity
o Do small change in true value invariably lead to changes in the measure value
I. Resolutiono What is the smallest change in the true value that can be detected?
II. Consistencyo Repeated measurement of same thing produce same results
Basis of sampling
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Contd..
B. Validity
The relation between a variable and what supposed to measure
I. Accuracy
o Free from systematic error
II. Specificity
o Describe that what it supposed to describe
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The main sampling techniques available to the marketing researcher are
summarized are as follows:
Probability based samples
1. Random samples-unrestricted and simple
2. Stratified samples
3. Cluster samples
4. Systematic sampling
Non-probability based samples
1. Quota
2. Convenience
Sampling Techniques
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Random samples
Generally preferred and produces more precise estimators
Unrestricted random sample.
Restricted random sample.
Avoid the problems of selection bias.
Two procedure for achieve true randomness
Lottery method
Random number method
Probability based samples
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Advantages
Ease calculation.
Benchmark method.
Disadvantages
Identify every single sampling units.
Enumerate the sampling units.
Establish physical contact.
Cont.…….
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Overcome restricted approaches random sampling difficulties.
Splitting population into strata(smaller populations).
Use the two approaches
Proportionate stratified sampling.
Disproportionate stratified sampling.
Use extensively for continuous research activities.
Unduly expensive on data collection.
Stratified Samples
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Similar to stratified sampling.
Cost effective method.
Major difference are:
Strata defined by selected characteristic – key independent variable (e.g. what year they’re in).
To ensure desired number of households in each district.
Cluster defined by spatial or social linkages – may not have anything to do with study (e.g. what class they’re in).
To make it easier to do door-to-door surveys.
Cluster sampling
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Advantages
Does not required a precise sampling frame.
Used frequently in conjunction with a geographic frame.
Economically more efficient than other random sample
Disadvantages
Statistically less efficient than other random sample.
Cont.…….
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Statistical method involving the selection of elements from an ordered sampling
frame. Most common form is an equal-probability method. In this approach, progression through the list is treated circularly, with a return to the
top once the end of the list is passed. The sampling starts by selecting an element from the list at random and then every kth
element in the frame is selected, where k, the sampling interval (sometimes known as
the skip). This is calculated as: k=N/n where n is the sample size, and N is the population size.
For eg:-population=2000, sample=200
K=2000/200 =10 , Here, random sample start = 7 then 7,17,27,37,…….1997.
Systematic sampling
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Systematic sampling can be divided into
One-stage cluster
E.g.:-one number the days of the week
Multi-stage cluster
E.g.:-population of farmer further stratifying into broad types.
In reality , multi-stage cluster is widely used in national surveys
Cont.…….
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All items in the universe do not have equal chance of being selected
Useful for quick and cheap studies
Potential for bias
“Inferior”
Quota Sampling and Convenience Sampling
Non Probability Based Sampling
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Advantages:
Less Time consumingLess expensiveRelatively less complex
Disadvantages:BiasnessQuestionable representativenessInaccurate
Contd.
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Respondents selected in accordance with population criteria
Two step process:
Develop control categories or quotas
Select sample elements from within the quotas
Proportion based sampling
Quota Sampling
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Quota Sampling
Management English Maths
Enrollment 80 10 10
Percentage 80 10 10
Quota (n=50) 36 7 7
Quota Sampling considered more scientific and systematic
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INTERLOCKING PARALLEL
Opportunistic Approach
Entirely focused on convenience of researcher
Helpful in hypothesis formulation
Suitable for when the resources are limited
Quick, convenient and less expensive
Convenience Sampling
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Define the objectives of the study
Define the relevant population or universe
Identify the sampling frame
Select a sampling procedure
Determine the sample size
Select the sample units
Data Collection
Planning a Sample Survey
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Sampling
Broad approach to sampling: Probabilistic, Non probabilistic
Proper planning of Survey
Determinants of the type of survey to use
Summary
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