The manager of a commuter rail transportation system was recently asked by her governing board to determine which factors have a significant impact on the demand for rides in the large city served by the transportation network. The system manager collected data on variables thought to be possibly related to the number of weekly riders on the city's rail system. The file P10_20.xlsx contains these data. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Enter your answers in thousands. For example, an answer of 1.234 thousand should be entered as 1.234, not 1,234. Round your answers to three decimal places, if necessary. Holding all else constant, ridership by approximately thousands when the price per ride rises by $1.00. Holding all else constant, ridership by approximately thousands when the population increases by 1,000. Holding all else constant, ridership by approximately thousands when the disposable per capita income rises by $1.00. Holding all else constant, ridership by approximately thousands when the parking rate rises by $1.00. What proportion of the total variation in the number of weekly riders is not explained by this estimated multiple regression equation? Round your answer to one decimal place, if necessary.
The manager of a commuter rail transportation system was recently asked by her governing board to determine which factors have a significant impact on the demand for rides in the large city served by the transportation network. The system manager collected data on variables thought to be possibly related to the number of weekly riders on the city's rail system. The file P10_20.xlsx contains these data.
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Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Enter your answers in thousands. For example, an answer of 1.234 thousand should be entered as 1.234, not 1,234. Round your answers to three decimal places, if necessary.
Holding all else constant, ridership by approximately thousands when the price per ride rises by $1.00.
Holding all else constant, ridership by approximately thousands when the population increases by 1,000.
Holding all else constant, ridership by approximately thousands when the disposable per capita income rises by $1.00.
Holding all else constant, ridership by approximately thousands when the parking rate rises by $1.00.
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What proportion of the total variation in the number of weekly riders is not explained by this estimated multiple regression equation? Round your answer to one decimal place, if necessary.
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