Exhibit 10-2
A manager of a hotel chain is interested in investigating whether there is a relationship between staff labor hours and bed-day occupancy incurred by a hotel in a month.The manager randomly selected 17 of the hotels in the chain across the country and recorded, for each of the hotels, the staff's total labor hours for the month of July and the number of bed-days of occupancy for that month. (A hotel has occupied one "bed-day" if one bed is occupied (rented)for an entire day.)The manager is interested in seeing if the labor hours incurred can be predicted from the number of bed-days of occupancy on a monthly basis.
The sample data were analyzed using Excel.Shown below is part of the regression analysis output.

-Refer to Exhibit 10-2.According to this regression analysis,if the number of bed-days increases by 200,what is the predicted change in the number of labor hours required for a given month?
A)a decrease of 5621.2
B)a decrease of 17.6
C)an increase of 223.5
D)an increase of 882.2

Question

Exhibit 10-2
A manager of a hotel chain is interested in investigating whether there is a relationship between staff labor hours and bed-day occupancy incurred by a hotel in a month.The manager randomly selected 17 of the hotels in the chain across the country and recorded, for each of the hotels, the staff's total labor hours for the month of July and the number of bed-days of occupancy for that month. (A hotel has occupied one "bed-day" if one bed is occupied (rented)for an entire day.)The manager is interested in seeing if the labor hours incurred can be predicted from the number of bed-days of occupancy on a monthly basis.
The sample data were analyzed using Excel.Shown below is part of the regression analysis output.
 
-Refer to Exhibit 10-2.According to this regression analysis,if the number of bed-days increases by 200,what is the predicted change in the number of labor hours required for a given month?
A)a decrease of 5621.2 
B)a decrease of 17.6 
C)an increase of 223.5 
D)an increase of 882.2

Quizplus · Accepted Answer

From the regression analysis output, we can see that the coefficient of the independent variable (bed-days of occupancy) is 1.1173. This means that for every one unit increase in bed-days of occupancy, there is an increase of 1.1173 units in labor hours. Therefore, if the number of bed-days increases by 200, the predicted change in labor hours would be:
200 x 1.1173 = 223.46
Rounding to one decimal place, the answer is an increase of 223.5 labor hours. Option C is the correct answer.

Exhibit 10-2 A Manager of a Hotel Chain Is Interested in Investigating