Exhibit 16.5.The following data shows the demand for an airline ticket dependent on the price of this ticket. For the assumed cubic and log-log regression models,Demand = β₀ + β₁Price + β₂Price² + β₃Price³ + ε and ln(Demand)= β₀ + β₁ln(Price)+ ε,the following regression results are available: Refer to Exhibit 16.5.Assuming that the sample correlation coefficient between Demand and is 0.956,what is the predicted demand for a price of $250 found by the model with better fit? A)4447.88 B)3914.38 C)4029.38 D)5137.60

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The Answer of Exhibit 16.5.The following data shows the demand for an airline ticket dependent on the price of this ticket. For the assumed cubic and log-log regression models,Demand = β₀ + β₁Price + β₂Price² + β₃Price³ + ε and ln(Demand)= β₀ + β₁ln(Price)+ ε,the following regression results are available: Refer to Exhibit 16.5.Assuming that the sample correlation coefficient between Demand and is 0.956,what is the predicted demand for a price of $250 found by the model with better fit? A)4447.88 B)3914.38 C)4029.38 D)5137.60