The occompanying dota file shows the price, the age, and the mileoge for 20 used sedans: click here for the Excel Dota File a. Estimate the sample regression equotion that enables us to predict the price of a sedan on the bosis of its oge and mileage. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal ploces. (If you are using R to obtain the output, then first enter the following command at the prompt: options(scipen-10). This will ensure that the output is not in scientific notation.] b. Interpret the slope coefficient of Age. The slope coefficient of Age is -621.80 , which suggests that for every additional year of age, the predicted price of car decreases by $62180. The slope coefficient of Age is -0.07 , which suggests that for every additional year of age, the predicted price of cor decreases by $0.07. The slope coefficient of Age is -621.80 , which suggests thot for every additional year of age, the predicted price of car decreases by $62180, holding number of miles constant. The slope coefficient of Age is -0.07 , which suggests thot for every additional year of age, the predicted price of car: b. Interpret the slope coefficient of Age. The slope coefficient of Age is -62180 , which suggents thot for every additional year of age, the predicted price of car decreoses by $62180 The slope coefficient of Age is -0.07 , which suggests that for every additional year of age, the predicted price of cor decreases by $0.07. The slope coefficient of Age is -62180; which suggests that for every additional year of oge, the predicted price of car decreases by $621.80, holding number of miles constant. The slope coefficient of Age is -0.07 , which suggests thot for every additional year of age, the predicted price of car decreases by $0.07, holding number of miles constant. c. Predict the price of a six-year-old sedon with 68,000 miles. Note: Do not round intermediate calculations. Round final answer to 2 decimal places. \begin{tabular}{|r|r|r|r|} \hline 1 & \multicolumn{1}{|c|}{ Price } & Age & Mileage \\ \hline 2 & 13611 & 4 & 61508 \\ \hline 3 & 13779 & 9 & 54308 \\ \hline 4 & 22987 & 3 & 8276 \\ \hline 5 & 153.49 & 7 & 24893 \\ \hline 6 & 16393 & 2 & 22109 \\ \hline 7 & 16596 & 2 & 23716 \\ \hline 8 & 16930 & 6 & 47443 \\ \hline 9 & 18489 & 3 & 16867 \\ \hline 10 & 18842 & 1 & 35371 \\ \hline 11 & 19813 & 1 & 29625 \\ \hline 12 & 11850 & 6 & 55769 \\ \hline 13 & 14977 & 5 & 46235 \\ \hline 14 & 15913 & 3 & 37024 \\ \hline 15 & 16492 & 5 & 45533 \\ \hline 16 & 9453 & 10 & 86891 \\ \hline 17 & 12972 & 4 & 77268 \\ \hline 18 & 15705 & 6 & 59603 \\ \hline 19 & 10519 & 9 & 93254 \\ \hline 20 & 8912 & 11 & 48233 \\ \hline 21 & 11913 & 9 & 42423 \\ \hline \end{tabular}