Author(s): P Srivyshnavi, SK Nafeez Umar, G Mokesh Rayalu, M Jahnavi, M Venkataramaniah and P Balasiddamuni

Abstract: Research is a method or process to discover truth based on practical or critical thinking. A plan to do research is a systematic manner is called Research Design. One of the important steps involved in planning Research design is ‘Data Analysis of Projects’ by using Statistical Tools or Techniques. Besides the basic statistical measures such as measures of central tendency and measures of variation, statistical inferential procedures will help to draw valid conclusions about the characteristics of the population on the basis of sample observations. The major areas of statistical inference are ‘Theory of Estimation’ and ‘Theory of Testing the Hypothesis’.
Researchers in the fields of Applied Sciences frequently collect measurements on several variables. Generally, univariate statistical tools may not be suitable to analyze multivariate data. Some advanced multivariate statistical tools which are analogous to univariate statistical tools are essential to analyze multivariate data. Multivariate analysis is an inherently difficult subject to understand by applied research workers. More mathematics is required to derive multivariate statistical techniques for drawing inferences than in a univariate setting.
Modern computer software statistical packages such as SPSS version-21, SAS, QSB, RATS, R-software etc., readily provide the numerical results to rather complex multivariate statistical analysis.
In the present research article, some advanced statistical tools for data analysis of Research Projects have been proposed for the purpose of Research workers in applied sciences.

Pages: 437-441 | Views: 1013 | Downloads: 17

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