mb0050 slides unit 07

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C o n f i d e n t i a l

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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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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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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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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 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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