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Data analytics on census data to predict the income and economic hierarchy

Author

Listed:
  • K.G. Srinivasa
  • R. Sharath
  • S. Krishna Chaitanya
  • K.N. Nirupam
  • B.J. Sowmya

Abstract

The US Census Bureau conducts the American Community Survey generating a massive dataset with millions of data points. The rich dataset contains detailed information of approximately 3.5 million households about who they are and how they live including ancestry, education, work, transportation, internet use and residency. This enormous data encourages the need to know more about the population and to derive insight. The ever demanding requirement in exposing the subtlety in case of economic issues is the motivation behind to construe meaningful conclusions in income domain. Hence the focus is to concentrate on bringing out unique insights into the financial status of the people living in the country. These conclusions delineated might aid in delivering wiser decisions in regard to economic growth of the country. Using relevant attributes, demographic graphs are plotted, aiding the conclusions drawn. Also classifications into various economic classes are done using well known classifiers.

Suggested Citation

  • K.G. Srinivasa & R. Sharath & S. Krishna Chaitanya & K.N. Nirupam & B.J. Sowmya, 2018. "Data analytics on census data to predict the income and economic hierarchy," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 10(3), pages 223-240.
    • Handle: RePEc:ids:injdan:v:10:y:2018:i:3:p:223-240
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