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Activity Number:
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433
- Contributed Poster Presentations: Business Analytics/Statistics Education Interest Group
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Type:
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Contributed
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Date/Time:
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Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
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Sponsor:
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Business Analytics/Statistics Education Interest Group
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Abstract #322378
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Title:
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Predictive and Representative Composite Score
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Author(s):
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Heungsun Park* and Seonwoong Eo and Young Rock Kim
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Companies:
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Hankuk University of Foreign Studies and Innovation Team, ILHWA Co. LTD and Hankuk University of Foreign Studeis
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Keywords:
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composite indicator;
canonical correlation;
best predictor;
nonlinear programing;
canonical correlation coefficient;
principal component analysis
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Abstract:
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Composite Score is made up of two or more variables that are highly related to one another conceptually and statistically, and it can be widely used as a predictor for future response variable once developed. This paper aims to develop new composite scoring systems with representing subordinate variables equally as possible whereas principal component analysis/factor analysis fails to do, and being highly correlated with a future variable. The presented methods can be applied to college entrance composite scores taking into account the future better college academic achievement (GPA), or developing the ranking scores for start-up companies using science and technology index scores with keeping in mind the future better stock performances.
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Authors who are presenting talks have a * after their name.
