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Data Minning Application into Potential Voters Trends in USA Elections with Regression Analysis

Author

Listed:
  • Olagunju Mukaila
  • Tomori Adekola Rasheed

Abstract

Background: Data Minning technique is very useful in bringing out the hidden information which is very useful to provide solution to a particular problem. Objective: The essence of this paper is to provide a basic model which relates potential voters in USA elections with periods of registration. Method: SPSS (Statistical Package for Social Sciences) is the choosen software and it was used to perform the analysis with Data Mining techniques, the raw data between 1932 to 2010 was refined and the data chosen which was twenty years were used for the analysis. With Data Mining Techniques through the linear regression analysis, the mathematical model which relate the voter’s registration in every two years. Result: Based on this model, it was discovered that there is relationship with potential voters or participant and years of registrations. Conclusion: Base on the findings,it was discurvered that the voting trend in USA election is baed on the population of the voters and the year or period also play significant role because as year incrases the population also increases.

Suggested Citation

  • Olagunju Mukaila & Tomori Adekola Rasheed, 2012. "Data Minning Application into Potential Voters Trends in USA Elections with Regression Analysis," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 2(12), pages 893-899.
    • Handle: RePEc:asi:joasrj:v:2:y:2012:i:12:p:893-899:id:3438
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