IEEE Style Citation: Saumya Gupta, Pradeep Rai, “Mapping Correlation between GDP and Poverty rate of India using Linear Regression,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.361-365, 2018.
MLA Style Citation: Saumya Gupta, Pradeep Rai "Mapping Correlation between GDP and Poverty rate of India using Linear Regression." International Journal of Computer Sciences and Engineering 6.5 (2018): 361-365.
APA Style Citation: Saumya Gupta, Pradeep Rai, (2018). Mapping Correlation between GDP and Poverty rate of India using Linear Regression. International Journal of Computer Sciences and Engineering, 6(5), 361-365.
BibTex Style Citation:
@article{Gupta_2018,
author = {Saumya Gupta, Pradeep Rai},
title = {Mapping Correlation between GDP and Poverty rate of India using Linear Regression},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {361-365},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1986},
doi = {https://doi.org/10.26438/ijcse/v6i5.361365}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.361365}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1986
TI - Mapping Correlation between GDP and Poverty rate of India using Linear Regression
T2 - International Journal of Computer Sciences and Engineering
AU - Saumya Gupta, Pradeep Rai
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 361-365
IS - 5
VL - 6
SN - 2347-2693
ER -
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Abstract
We aim to project the impact of the Gross Domestic Product of India on the overall poverty rate of the country through the trailing years using data science. The correlation between GDP and Poverty rates has been modelled for the years 1981-2015. On getting a high correlation, we have used Linear Regression in order to train a model corresponding to the World development Indicators (a world-bank dataset) and found out their individual contributions towards the GDP of the country. The results found during the research are immensely helpful to define the major contributors of the current economic conditions of India. Also, these results can be further formulated to predict the poverty rates of the country.
Key-Words / Index Term
GDP(Gross Domestic Product), Poverty rates, Data Science, Pearson’s correlation, Linear regression
References
[1] Deaton, Angus. 2010. "Price Indexes, Inequality, and the Measurement of World Poverty." American Economic Review, 100 (1): 5-34.DOI: 10.1257/aer.100.1.5
[2] Sanjay G. Reddy, “Counting the poor: the truth about world poverty statistics”
[3] Human Development Reports, United Nations development program.
[4] Martin Ravallion, “Poverty Lines in Theory and Practice”, Georgetown University
[5] Dong Nguyen Noah A. Smith Carolyn P. Rose,
“Author Age Prediction from Text using Linear Regression”, Language Technologies Institute Carnegie Mellon University, Pittsburgh, PA 15213, USA
[6] Christofides, S., Regression Models Based on Log-incremental Payments, Claims Reserving Manual,
1990.2, Institute of Actuaries, London.
[7] World Development Indicators | A World Bank data published by Kaggle.
[8] GDP World Bank Data | A world bank data published by Kaggle
[9] Statista – The statistics portal for market data, market research and market studies.
[10] Ieconomics | Search and visualization of economic indicators.
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