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Program : MBA
Semester : III
Subject Code : MB0050
Subject Name : Research Methodology
Unit Number : 7
Unit Title : Sampling
Lecture Number : 7
Lecture Title : Sampling
Book Id : B1700
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Sampling
Objectives :
Explain the basic concepts of sampling.
Distinguish between sample and census.
Differentiate between a sampling and non-sampling error.
Understand the meaning of sampling design.
Explain different types of probability sampling designs.
Describe various types of non-probability sampling designs.
Estimate the sample size required while estimating the population
mean and proportion.
In this unit, we will discuss in detail the concept of sampling,
including sampling and non-sampling error, probability and non-
probability sampling designs, as well as determination of sample
size.2
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Unit-7 Sampling
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Lecture Outline
Introduction
Sampling Concepts
Sampling Design
Determination of Sample Size
Summary
Check Your Learning
Activity
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Introduction
Once the information needs are specified, the sources of collecting
the information are sought. Some information may be collected
through secondary sources whereas the rest may be obtained
through primary sources.
The primary methods of collecting information could be the
observation method, personal interview with questionnaire,telephone surveys and mail surveys.
Surveys are useful in information collection and survey
respondents should be selected using the appropriate procedures;
otherwise the researchers may not be able to get the right
information to solve the problem under investigation. This is done
through sampling.
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Sampling Concepts
Sampling involves the study of a small number of individuals, objects
chosen from a larger group.
Some of the sampling concepts are:
Population: Refer to any group of people or objects that form the subject of
study in a particular survey.
Sampling frame: Comprises all the elements of a population with proper
identification for selection at any stage of sampling.
Sample: Subset of the population and comprises some elements of the
population.
Sampling unit: A single member of the sample
Census (or complete enumeration): An examination of each and every
element of the population is called census or complete enumeration.
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Sampling Concepts
Sample vs Census:
If all the households in a population are asked to provide information,
such a survey is called a census.
There is an alternative way of obtaining the same information, by
choosing a subset of all the two lakh households and asking them for the
same information. This subset is called a sample.
Advantages of sample over census.
Sample saves time and cost
There are situations where a sample is the only option.
The study of a sample instead of complete enumeration may, at times, produce
more reliable results.
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Sampling Concepts
Sampling vs Non-Sampling Error
Sampling error arises when a sample is not representative of the
population. It is the difference between sample mean and population
mean.
Non-sampling error arises not because a sample is not a representative
of the population but because of other reasons.
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Sampling Design
Sampling design refers to the process of selecting samples from a
population. There are two types of sampling designsprobability
sampling design and nonprobability sampling design.
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Unit-7 Sampling
ProbabilitySamplingDesign
Simple random sampling with
replacement (SRSWR) Simple random samplingwithout replacement (SRSWOR)
Systematic sampling
Stratified random sampling
Non-probabilitySamplingDesigns
Convenience sampling Purposive (judgmental) sampling
Snowball sampling
Quota sampling
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Determination of Sample Size
The size of a sample depends upon the basic characteristics of the
population, the type of information required from the survey and the
cost involved. Therefore, a sample may vary in size for several
reasons.
Methods of determining the sample size in practice:
Researchers may arbitrarily decide the size of sample
If the cost of sampling per sample unit is known, one can easily obtain the
sample size by dividing the total budget allocation by the cost of sampling
per unit.
There are researchers who decide on the sample size based on that was
done by other researchers in similar studies.
The most commonly used approach for determining the size of sample is
the Confidence interval approach covered under inferential statistics.
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Determination of Sample Size
Sample size for estimating population mean
The formula for determining the sample size in such a case is given by
Where X = e = Margin of error
n = Sample size
= Population standard deviation
Z = the value of standard normal ordinate
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Determination of Sample Size
Determination of sample size for estimating the population
proportion
The formula for determining the sample size in such a case is given by
The above formula will be used if the value of population proportion (proportionof occurrence of the event) p is known. If, however, p is unknown, we
substitute the maximum value of pq in the above formula. It can be shown that
the maximum value of pq is 1/4 when p = 1/2 and q = 1/2.
Therefore,
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Summary
Surveys are useful in information collection. The survey respondents should
be selected using appropriate and right procedures. The process of selecting
the right individuals, objects or events for the study is known as sampling.
An alternative to sample is census where each and every element of the
population (universe) is examined. There are many advantages of sampling
over complete enumeration.
The process of selecting samples from the population is referred to as
sampling design. There are two types of sampling designsprobability
sampling design and non-probability sampling design.
There are four probability sampling designsthe simple random sampling
with replacement, simple random sampling without replacement, systematic
sampling and stratified random sampling.
Under the non-probability sampling designs, there are convenience
sampling, judgmental sampling and snowball sampling.
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Check Your Learning
1. Differentiate between sample and census.
Ans: A census is a complete enumeration of the population, while a sample is asubset of the population.
2. Differentiate between the stratified random sampling and systematic
sampling.
Ans: Systematic sampling and stratified random sampling are types of
probability sampling design.
Stratified random sampling: Under this sampling design, the entire population
(universe) is divided into strata (groups), which are mutually exclusive and
collectively exhaustive.
Systematic sampling: In this design, the entire population is arranged in a
particular order.
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Activity
Visit a factory where there are unskilled, semiskilled and skilled
workers. If you have to choose a representative sample to examinetheir job satisfaction level, which sampling design would you choose
for the study? Justify your answer.
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