• Story Name: Quarterly Appliance Sales
  • Story Topics: Consumer, Economics,
  • Datafile Name: Quarterly Appliance Sales
  • Methods: Dummy Variable, Regression, Residuals, Time Series,
  • Abstract:

    The data presented in the datafile Quarterly Appliance Sales are suitable for developing models for predicting the four kinds of appliance sales. Three kinds of models can be developed. These are:

    1. A model with appropriate quarterly indicators, a time variable, coincident and lagged values of DUR or RES, and appropriate lagged values of the dependent variable.

    2. A model using only predictor variables which lead the dependent appliance series (delete from #1 coincident values of DUR or RES).

    3. A model using only appropriate seasonal indicators and lagged values of the dependent appliance series (delete from #2 lagges values of DUR or RES).

    For each model type considered, create a suitable model and test the resulting residuals for independence with time. If the residuals fail the test of independence with time, you may wish to add lagged values of residuals to your model. Compare the standard errors of estimate from your various models.

    For comparing forecasts with actual values, the values of the apppliance sales series for 1986 are

                   Quarter         DISH        DISP        FRIG        WASH
    
                         1                898       1063        1274          1297
                         2                955       1028        1822          1399
                         3              1008       1073        1932          1575
                         4              1054       1089        1494          1495  
    

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