medflydaylivingmort.rate012036460112036460.0014212019130.004311970980.0051411910200.0064511834190.0075611745020.0098711630260.0123811486930.0164911298360.02181011051640.02981110722090.03791210316200.0452139849800.0589149270110.0634158682020.0722168054890.0757177445200.0793186855140.0826196288660.085205754200.0923215223190.0968224717560.1002234244690.1059
Audit Trail - Statistics Accuracy MeasuresValue AIC233.07 BIC234.66 Mean Absolute Percentage Error (MAPE)0.48%R-Square95.45%Adjusted R-Square93.50%Mean Square Error45,021,570.00 Root Mean Square Error6,709.81 Theil0.53 Method StatisticsValue Method SelectedGompertz
Curve Minimum0.00 Maximum1,197,093.36 The first 23 observations in a data set involving the mortality of medflies is shown above. The column titled "living" indicates the number of living flies in each day of the experiment.Consider that you wish to predict the outcome of the experiment only ten days into the experiment. That is, you wish to forecast when the last medfly will expire. You do so with the model shown above.The model chosen for this estimation was probably chosen because
A. there is no offsetting factor hindering the attainment of the endpoint.
B. declining values are always estimated using this type of model.
C. there may be an offsetting factor such that growth is more difficult to maintain as the endpoint is approached.
D. growth can never be negative.
E. None of the options are correct.
Answer: C
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