A manager of a car rental chain was interested in investigating if there is a relationship between monthly labor hours and the number of cars rented.The officer randomly selected 17 of the car rental locations in the chain across the country and recorded, for each of these car rental locations the monthly labor hours required during the month of July and the number of cars rental days for that month. (A car rental has rented a car one "rental day" if one car is "rented" for an entire day.) The officer is interested in seeing if the labor hours required can be predicted from the number of cars rented on a monthly basis.

Included below is part of the regression analysis output, which I created based on a sample.

According to this regression analysis, if the number of car rental days increases by 300, what is the predicted increase in the number of labor hours required for a given month?

Please show the calculations used to reach the answer so I can understand the process.

SUMMARY OUTPUT Re. ression tatistics Multiple R 0984982734 R Square 0.971171769 Adjusted R Square 0.979317217 Standard Error 846.7303978 Observations 17 ANOVA df M F in nificancd F Regression 1 370836819 379836819 413.1055672 3.30971E-12 Residual 15 1265089136 906359.0535 Total 16 483698113 oef'ficients tandard Error t tat Pvalue Intercept -27.094770 308.9252643 -0.077085053 0.820854518 Bed Days 1.106278321 0.037792184 2278466750 3.30971 E-12