Mapping Correlation between GDP and Poverty rate of India using Linear Regression
DOI:
https://doi.org/10.26438/ijcse/v6i5.361365Keywords:
GDP(Gross Domestic Product), Poverty rates, Data Science, Pearson’s correlation, Linear regressionAbstract
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.
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Statista – The statistics portal for market data, market research and market studies.
Ieconomics | Search and visualization of economic indicators.
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