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Factor Analysis of Population Growth using Data Analytics

Anupama Girish1 , Aditya Dey2 , Ankit Sharma3 , Ketan Jain4 , Kumar Sanket5 , Amutha S.6 , Ramesh Babu. D.R7

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 422-425, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.422425

Online published on Sep 30, 2018

Copyright © Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R, “Factor Analysis of Population Growth using Data Analytics,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.422-425, 2018.

MLA Style Citation: Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R "Factor Analysis of Population Growth using Data Analytics." International Journal of Computer Sciences and Engineering 6.9 (2018): 422-425.

APA Style Citation: Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R, (2018). Factor Analysis of Population Growth using Data Analytics. International Journal of Computer Sciences and Engineering, 6(9), 422-425.

BibTex Style Citation:
@article{Girish_2018,
author = {Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R},
title = {Factor Analysis of Population Growth using Data Analytics},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {422-425},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2884},
doi = {https://doi.org/10.26438/ijcse/v6i9.422425}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.422425}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2884
TI - Factor Analysis of Population Growth using Data Analytics
T2 - International Journal of Computer Sciences and Engineering
AU - Anupama Girish , Aditya Dey, Ankit Sharma, Ketan Jain, Kumar Sanket, Amutha S., Ramesh Babu. D.R
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 422-425
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

According to the estimation billionth person was born in 1804 and the second billionth was born about 123 years later in 1927. Since then it has taken humans 60 years to reach the 5 billion mark and now we are closer to population of 8 billion. India contributes about 20% of this population making it as the second most populous country in the world. Originally, most of the important predictions were made using the Malthusian growth models. The science of data analytics has opened up new possibilities in the creation of prediction graphs. Prediction graphs give useful information about tackling the problem of increasing population. R programming language is used to identify factors that impact the rate of change of population. Important factors such as literacy rate, death rate, religion and so on, deeply impact the rate of population growth. From the Kaiser-Meyer-Olkin test and Factor Analysis found that out of all factors that were considered, religious differences and migration rate were the most important factors affecting the rate of population growth.

Key-Words / Index Term

Malthusian growth model,Data Analytics, Factors, R-Programmimg language, Kaiser-Meyer-Olkin

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