Chapter 2 Sources of Data

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Chapter 2

Sources of DataIbrahim Sameer (MBA - Specialized in Finance,

B.Com Specialized in Accounting & Marketing)

www.ibrahimsameer.wordpress.com


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Types of Data

Data may be classified as follows:

Primary

Secondary

Discrete

Continuous


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Types of Data

Primary data are data collected especially for a

specific purpose. Raw data are primary data

which have not been processed at all, and whichare still just a list of numbers.

For Eg: Telephone survey conduct by Dhiraagu to

monitor the effectiveness of the customer service.


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Types of Data

Secondary data are data which have already

been collected elsewhere, for some other

purpose, but which can be used or adapted for thesurvey being conducted.

Eg: Annual Statistics published by Department of

National Planning in the Maldives.


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Types of Data

Discrete data are data which can only taken on a

finite or countable number of values within a

given range. For example goals scored by Arsenal against

Chelsea in the FA cup final: Arsenal could score

0,1,2,3 or even 4 but they cannot score 1 or 2

goals.


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Types of Data

Continuous data are data which can take on any

values.They are measured rather than counted.

For example the heights of all members of yourfamily, as these can take on any value 1.542m,

1.696m, and 1.923m


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Types of Data


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Sources of Data

Data may be obtained from an internal sources or

an externalsources.

Internal data include such as accountinginformation, data relating to employees, much data

will be produced by a production department.


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Sources of Data

External data come in two form that is primary and

secondary data.


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Sources of Data

The main source of secondary data are:

government, banks, newspapers, trade

journals, information bureaux, consultancies,

libraries and information service.


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Sampling

Data are often collected from a samplerather than

from a population. If the whole population is

examined, the survey is called census.


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Sampling method

A probability sampling method is a sampling

method in which there is a known chance of each

memember of the population appearing in the

sample.


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Sampling method

Probability sampling methods include the

following:

Random

Stratified random

Systematic

Multistage

Cluster


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Sampling method

Random sampling

A simple random sample is a sample selected in

such a way that every item in the population hasan equal chance of being included.


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Sampling method

Sampling frames

If random sampling is used then it is necessary to

construct a sampling frame.

A sampling frame is a numbered list of all items

in a population. Sampling frame is required in

Random, Stratified random, Systematic, Multistage

& Cluster sampling.


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Sampling method

Drawback of Random sampling

An adequate sampling frame might not exist.

It might be costlyto obtain the data if the selected

items cover a wide range.


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Sampling method

Stratified random sampling

Stratified random sampling is a method of

sampling which involves dividing the populationinto strata or categories. Random samples are

then taken from each stratum or category.


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Sampling method

Advantages of Stratified random sampling

The samples selected will be representative.

The structure of the sample will reflect that of the

population.

Precisionis increased.


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Sampling method

Disadvantages of Stratified random sampling

Required prior knowledge of each item in the

population.


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Sampling method

Systematic sampling

Systematic sampling is a sampling method which

works by selecting every nth item after a random

start.


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Sampling method

Advantages of Systematic sampling

It is easy to use

It is cheap


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Sampling method

Disadvantages of Systematic sampling

It is possible that a biased sample might be

chosen if there is a regular pattern to the

population which coincides with the sampling

method.

It is not completely random since some items

have a zero chance of being selected.


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Sampling method

Multistage sampling

Multistage sampling is a probability sampling

method which involves dividing the population

into a number of sub-populations and then

selecting a small sample of these sub-population

at random.


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Sampling method

Advantages of Multistage sampling

Fewer investigators are needed.

It is not so costly to obtain a sample.


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Sampling method

Disadvantages of Multistage sampling

Possibility of bias

This method is not truly random.


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Sampling method

Cluster sampling

Cluster sampling is a non random sampling

method that involves selecting one definable

subsection of the population as the sample, the

subsection taken to be representative of the

population in question.


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Sampling method

For eg: the pupils of one school might be taken as

a cluster sample of all children at school in one

country.


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Sampling method

Advantages of Cluster sampling

It is a good alternative to multistage sampling if

a satisfactory sampling frame does not exist.

It is inexpensiveto operate.


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Sampling method

Disadvantages of Cluster sampling

There is potential for considerable bias.


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Sampling method

Non probability sampling method

A non probability sampling method is a sampling

method in which the chance of each member of

the population appearing in the sample is not

known.


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Sampling method

Quota sampling

In quota sampling, randomness is forfeited in the

interest of cheapness and administrative

simplicity. Investigators are told to interview all

the people they meet up to a certain quota.


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Sampling method

Advantages of Quota sampling

It is cheapand administratively easy

A much larger sample can be studied

No sampling frame is necessary

It yield enough accurateinformation


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Sampling method

Disadvantages of Quota sampling

Bias

Sampling error


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Questions & Answers


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Thank You

Ibrahim SameerSeek knowledge from cradle to grave

Chapter 2 Sources of Data

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