Application of Discriminant Analysis: For Developing a Classification Model

J. P. Verma ()
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J. P. Verma: Lakshmibai National University of Physical Education, Research and Advanced Studies

Chapter Chapter 12 in Data Analysis in Management with SPSS Software, 2013, pp 389-412 from Springer

Abstract: Abstract Often we come across a situation where it is interesting to know as to why the two naturally occurring groups are different. For instance, after passing the school, the students can opt for continuing further studies, or they may opt for some skill-related work. One may be interested to know as to what makes them to choose their course of action. In other words, it may be desired to know on what parameters these two groups may be distinct. Similarly one may like to identify the parameters which distinguish the liking of two brands of soft drink by the customers or which make the engineering and management students different. Thus, to identify the independent parameters responsible for discriminating these two groups, a statistical technique known as discriminant analysis (DA) is used. The discriminant analysis is a multivariate statistical technique used frequently in management, social sciences, and humanities research. There may be varieties of situation where this technique can play a major role in decision-making process. For instance, the government is very keen that more and more students should opt for the science stream in order to have the technological advancement in the country. Therefore, one may investigate the factors that are responsible for class XI students to choose commerce or science stream. After identifying the parameters responsible for discriminating a science and commerce student, the decision makers may focus their attention to divert the mindset of the students to opt for science stream.

Keywords: Discriminant Analysis; Discriminant Function; Canonical Correlation; Discriminant Model; Multivariate Statistical Technique (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-81-322-0786-3_12

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