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The following data show 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.
Assuming that the sample correlation coefficient between Demand and
= exp(26.3660 - 3.2577 ln(Price) + (0.2071) 2/2) is 0.956, what is the predicted demand for a price of $250 found by the model with better fit?
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