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  • Topic: Sampling, Stratified sampling, Sample
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Methods of Sampling

An

Individual Assignment

In

Business Maths II

SYBBA

Submitted by:
Shweta Thapa R-11-35

Department of Business Administration
Rosary College of Commerce & Arts
2013-2014

A simple random sample
A simple random sample is obtained by choosing elementary units in search a way that each unit in the population has an equal chance of being selected. A simple random sample is free from sampling bias. However, using a random number table to choose the elementary units can be cumbersome. If the sample is to be collected by a person untrained in statistics, then instructions may be misinterpreted and selections may be made improperly. Instead of using a least of random numbers, data collection can be simplified by selecting say every 10th or 100th unit after the first unit has been chosen randomly as discussed below. Such a procedure is called systematic random sampling.

Systematic Sampling
Systematic sampling is a frequently used variant of simple random sampling. When performing systematic sampling, every kith element from the list is selected (this is referred to as the sample interval) from a randomly selected starting point. For example, if we have a listed population of 6000 members and wish to draw a sample of 2000, we would select every 30th (6000 divided by 200) person from the list. In practice, we would randomly select a number between 1 and 30 to act as our starting point.

A stratified sample
A stratified sample is obtained by independently selecting a separate simple random sample from each population stratum. A population can be divided into different groups may be based on some characteristic or variable like income of education. Like anybody with ten years of education will be in group A, between 10 and 20 group B and between 20 and 30 group C. These groups are referred to as strata. You can then randomly select from each stratum a given number of units which may be based on proportion like if group A has 100 persons while group B has 50, and C has 30 you may decide you will take 10% of each. So you end up with 10 from group A, 5 from group B and 3 from group C.

A cluster sample
A cluster sample is obtained by selecting clusters from the population on the basis of simple random sampling. The sample comprises a census of each random cluster selected. For example, a cluster may be something like a village or a school, a state. So you decide all the elementary schools in New Delhi are clusters. You want 20 schools selected. You can use simple or systematic random sampling to select the schools, and then every school selected becomes a cluster. Merits and demerits of Random sampling method

Merits
(i) Scientific Technique:
It provides a scientific technique of selecting the sample from a universe in which each unit of the universe has the equal chance of being included in the sample. (ii) Less chance of Bias:
There is little chance of bias and prejudices of investigator to play and influence the selection of the sample. (iii) Based on Probability:
This method is based on the theory of probability which is a mathematical concept and as such it is quite possible to determine the sample error under this method. (iv) More Accuracy:
It is possible to lay down the degree of accuracy achieved' the investigation conducted by this method. (V) Suitable for Large Numbers: It is quite suitable in case of large sampling where the size of both the sample and the universe is very large. (vi) Less dependence on detailed Information:

It does not depend very much upon the existence of detailed information about the universe for its effectiveness. (vii) Evaluation of Relative Efficiency:
It is possible to evaluate the relative efficiency of various sample designs when conducted under this method. Demerits
(i) Expensive:
It is highly expensive and time taking.
(ii) Requires More Skill:
It needs a very high level of skill and experience on the; part of the...
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