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simplifying data, which are otherwise quite unwieldy and voluminous. It seeks to
achieve this in a manner that meaningful conclusions can be readily drawn from the
data. Descriptive statistics may thus be s een as comprising methods of bringing out
and highlighting the latent characteristics pr esent in a set of numerical data. It not
only facilitates an understand ing of the data and systematic reporting thereof in a
manner; and also makes them amenable to further discussion, analysis, and
interpretations.
The first step in any scientific inquiry is to collect data relevant to the problem in
hand. When the inquiry relates to physical and/or biologic al sciences, data collection
is normally an integral part of the experime nt itself. In fact, the very manner in which
an experiment is designed, determines the kind of data it w ould require and/or
generate. The problem of identif ying the nature and the kind of the relevant data is
thus automatically resolved as soon as th e design of experiment is finalized. It is
possible in the case of physical sciences. In the case of social sciences, where the
required data are often collected through a questionnaire from a number of carefully
selected respondents, the problem is not that simply resolved. For one thing,
designing the questionnaire itself is a critical initial pr oblem. For another, the number
of respondents to be accessed for data colle ction and the criteria for selecting them
has their own implications and importance fo r the quality of results obtained. Further,
the data have been collected, these are assembled, organized, and presented in the
form of appropriate tables to make th em readable. Wherever needed, figures,
diagrams, charts, and graphs are also used for better presentation of the data. A useful
tabular and graphic presentation of data wi ll require that the raw data be properly
classified in accordance with the objectives of investigation and the relational analysis
to be carried out. .

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