• DocumentCode
    2230574
  • Title

    Successful Forecasting for Knowledge Discovery by Statistical Methods

  • Author

    Alsultanny, Yas

  • Author_Institution
    Coll. of Grad. Studies, Arabian Gulf Univ., Manama, Bahrain
  • fYear
    2012
  • fDate
    16-18 April 2012
  • Firstpage
    584
  • Lastpage
    588
  • Abstract
    The importance of statistical forecasting is in its ability to discover hidden knowledge from databases. Forecasting is used successfully in many sectors. In this paper, forecasting is implemented in the educational sector, three time series algorithms are used, namely-simple moving average forecasting, weighted average forecasting and linear trend forecasting. Six secondary schools (from 7th to 9th) were selected in this study and data was collected for 9 years. The results indicate that the linear trend forecasting was the most accurate in predicting the school success ratio compared with the simple moving average forecasting and weighted average forecasting, as far as mean absolute error, mean square error and absolute percentage error are concerned.
  • Keywords
    data mining; educational institutions; forecasting theory; mean square error methods; statistical analysis; time series; absolute percentage error; educational sector; hidden knowledge discovery; linear trend forecasting; mean absolute error; mean square error; school success ratio; secondary schools; simple moving average forecasting; statistical forecasting; time series algorithms; weighted average forecasting; Accuracy; Educational institutions; Forecasting; Mathematical model; Predictive models; Standards; Time series analysis; linear trend forecasting; school sucessful ratio; simple moving average; time series algorithms; weighted average;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2012 Ninth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4673-0798-7
  • Type

    conf

  • DOI
    10.1109/ITNG.2012.160
  • Filename
    6209215