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The Following Data Show the Demand for an Airline Ticket

question 107

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The following data show the demand for an airline ticket dependent on the price of this ticket. 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 = β<sub>0</sub> + β<sub>1</sub>Price + β<sub>2</sub>Price<sup>2 </sup>+ β<sub>3</sub>Price<sup>3 </sup>+ ε and ln(Demand) = β<sub>0</sub> + β<sub>1</sub>ln(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) <sup>2</sup>/2) is 0.956, what is the predicted demand for a price of $250 found by the model with better fit? A) 4,447.88 B) 3,914.38 C) 4,029.38 D) 5,175.09 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. 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 = β<sub>0</sub> + β<sub>1</sub>Price + β<sub>2</sub>Price<sup>2 </sup>+ β<sub>3</sub>Price<sup>3 </sup>+ ε and ln(Demand) = β<sub>0</sub> + β<sub>1</sub>ln(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) <sup>2</sup>/2) is 0.956, what is the predicted demand for a price of $250 found by the model with better fit? A) 4,447.88 B) 3,914.38 C) 4,029.38 D) 5,175.09 Assuming that the sample correlation coefficient between Demand and 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 = β<sub>0</sub> + β<sub>1</sub>Price + β<sub>2</sub>Price<sup>2 </sup>+ β<sub>3</sub>Price<sup>3 </sup>+ ε and ln(Demand) = β<sub>0</sub> + β<sub>1</sub>ln(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) <sup>2</sup>/2) is 0.956, what is the predicted demand for a price of $250 found by the model with better fit? A) 4,447.88 B) 3,914.38 C) 4,029.38 D) 5,175.09 = 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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