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Study on WeightedNon-Weighted Regression Curves for the Population with Diabetes Mellitus

Undergraduate #357
Discipline: Science and Mathematics Education
Subcategory:

Dhruvika Patel - Savannah State University


This study mainly addresses the development of a new numerical approach to depict the number of patients. Based on the discrete dataset of the numbers of national and international population with diabetes Mellitus from 1980 through 2015, we predict the number of future patients (in 2040) by using linear and nonlinear exponential regression curves obtained through the Least Square methods. Moreover, in order to emphasize the strong influence of more recent year data, we suggest the weighted Least Square Method whose weight is developed based on the standard logistic function. Finally we analyze the each results and seek for the further work.

Funder Acknowledgement(s): Chellu S. Chetty, Associate VP of Research and Sponsored Programs, Savannah State University; Devi Chellu, NIH-MARC U* STAR/RISE Program /NSF-PSLSAMP Program Manager, Savannah State University.

Faculty Advisor: Hyounkyun Oh, hoh@savannahstate.edu

Role: My Mentor and I worked together. He taught me equations and formulas than I worked on maple to find solution. I also collated data set of the numbers of national and International population with diabetes mellitus.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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