Marriott Corporation is considering building a new hotel conference center on a beachfront area of Venezuela. Before choosing the final location for the hotel/conference center complex, the management team acquired occupancy data and measured the proximity to the beach for 14 existing hotels in the area. The management team recognizes that the relationship between distance from the beach and occupancy rate must be known in order to predict the success of the new complex. The data are shown below.
Hotel Distance Occupancy rate
1 0.1 92
2 0.1 95
3 0.2 96
4 0.3 90
5 0.4 89
6 0.4 86
7 0.5 90
8 0.6 83
9 0.7 85
10 0.7 80
11 0.8 78
12 0.8 76
13 0.9 72
14 0.9 75
Summary Output
Regression Statistics
Multiple R 0.943618
R Square 0.890416
Adjusted R Square 0.881284
Standard Error 2.641994
Observations 14
|
df
|
SS
|
MS
|
F
|
Significance F
|
|
|
Regression
|
1
|
680.5956
|
680.5956
|
97.50469
|
4.1E-07
|
|
|
Residual
|
12
|
83.76158
|
6.980132
|
|
|
|
|
Total
|
13
|
764.3571
|
|
|
|
|
|
|
|
|
|
|
|
|
Coefficients
|
Standard Error
|
t Stat
|
P-Value
|
Lower 95%
|
Upper 95%
|
|
Intercept
|
98.25204
|
1.535711
|
63.97819
|
1.41E-16
|
94.90602
|
101.5981
|
|
X Variable1
|
-25.4768
|
2.580078
|
-9.87445
|
4.1E-07
|
-31.0983
|
-19.8553
|
1. Find (specify) the best model to predict the occupancy rate of the hotel complex.
2. Identify and define the slope and the y-intercept.
3. Predict the occupancy based on location 0.65 miles from the ocean.
4. How accurate is the model? How well does it explain occupancy? Discuss.
5. Is the model significant at the 0.05 level of significance? The critical value is 3.95.