The manager of a commuter rail transportation system was recently asked by her governing board to predict the demand for rides in the large city served by the transportation network. The system manager has collected data on variables thought to be related to the number of weekly riders on the city’s rail system. The file P10_20.xlsx contains these data. a. Estimate a multiple regression equation using all of the available explanatory variables.

Let X1 represent the year.
Let X2 represent the price per ride.
Let X3 represent the population.
Let X4 represent the income.
Let X5 represent the parking rate.

If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)

Ŷ =
+
X1 +
X2 +
X3 +
X4 +
X5

What does the ANOVA table indicate for this model?

Because of the
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p-value for the F test of this model, we
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conclude that this set of explanatory variables is
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in explaining the variation in Weekly Riders.

b. Is there evidence of auto correlated residuals in this model? Round your answer to two decimal places, if necessary.

The Durbin-Watson statistic for the residuals is
. This indicates that there might be a problem with
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lag 1 autocorrelation.