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Student Data Analysis using Clustering Approach

Published on February 2013 by Prasanna S. Karmarkar, Kavita S. Oza
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International Conference on Recent Trends in Information Technology and Computer Science 2012
Foundation of Computer Science USA
ICRTITCS2012 - Number 3
February 2013
Authors: Prasanna S. Karmarkar, Kavita S. Oza
860d68a1-4ae8-496c-999f-5015f5f1fbc3

Prasanna S. Karmarkar, Kavita S. Oza . Student Data Analysis using Clustering Approach. International Conference on Recent Trends in Information Technology and Computer Science 2012. ICRTITCS2012, 3 (February 2013), 23-26.

@article{
author = { Prasanna S. Karmarkar, Kavita S. Oza },
title = { Student Data Analysis using Clustering Approach },
journal = { International Conference on Recent Trends in Information Technology and Computer Science 2012 },
issue_date = { February 2013 },
volume = { ICRTITCS2012 },
number = { 3 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 23-26 },
numpages = 4,
url = { /proceedings/icrtitcs2012/number3/10263-1356/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Information Technology and Computer Science 2012
%A Prasanna S. Karmarkar
%A Kavita S. Oza
%T Student Data Analysis using Clustering Approach
%J International Conference on Recent Trends in Information Technology and Computer Science 2012
%@ 0975-8887
%V ICRTITCS2012
%N 3
%P 23-26
%D 2013
%I International Journal of Computer Applications
Abstract

The work developed shows that Cluster Analysis appropriately answers the questions that arise when we try to frame socially and pedagogically the success/failure in a particular subject. Proposed worked developed a logistic regression analysis, as the study was carried out as a contribution to explain the success/failure in Exams. As a final step, the responses of both statistical analysis were studied

References
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Index Terms

Computer Science
Information Sciences

Keywords

Student Data