Question
Let's re-examine the information presented previously in problem 2. Following are the number of victories for the Blue Sox and the hotel occupancy rate for
Let's re-examine the information presented previously in problem 2. Following are the number of victories for the Blue Sox and the hotel occupancy rate for the past eight years. You have been asked to test two forecasting methods to see which method provides a better forecast for the Occupancy Rate. The forecasting methods to test are to see whether Occupancy Rate is a) a function of time or b) a function of the Number of Blue Sox Wins.
Year | Number of Blue Sox Wins | Occupancy Rate |
1 | 70 | 78% |
2 | 67 | 83 |
3 | 75 | 86 |
4 | 87 | 85 |
5 | 87 | 89 |
6 | 91 | 92 |
7 | 89 | 91 |
8 | 85 | 94 |
For the following, calculate all forecasts to one decimal place (example, 93.2%)
a) Suppose we believe that there is a linear relationship between the Year and the Occupancy Rate. Develop a forecast for the Occupancy Rate assuming that this relationship is valid. What is this relationship and what is the forecast for the Occupancy Rate for Year 10?Provide both the appropriate regression relationship and the forecast.
b) Now, suppose that we believe that there is a linear relationship between the Number of Blue Sox Winsand the Occupancy Rate. What is this relationship and what is the forecast for the Occupancy Rate if the Number of Blue Sox Winsis 98 wins? What caution(s) would you recommend about using the linear regression relationship for predicting the occupancy rate for this number of wins? Provide both the appropriate regression relationship and the forecast.
c) How strong are the relationships you found in both a) and b)? You are wondering if either of these should be considered - not which is better. Would you recommend using either of these relationships for forecasting? Why?
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