The Keener Hotel in Tampa, Florida, is a luxury hotel that has 414 rooms. The hotel’s controller imported its monthly occupancy data from the past several years into Excel. The data includes month, year, room nights sold, average monthly high outdoor temperature, and monthly occupancy costs. Management would like to be able to predict monthly occupancy costs.

The following is an example of the records in that Excel file. Access the full data set online in the MyLab Accounting exercise.

Requirements
1. Perform a simple linear regression using Room nights sold as the independent variable and Occupancy costs as the dependent variable.
2. Perform a multiple regression using Room nights sold and Average monthly high temperature as the independent variables and Occupancy costs as the dependent variable.
3. Assume that management expects to sell 10,500 room nights in a month when the average daily high outdoor temperature is expected to be 78 degrees. Predict the hotel’s occupancy costs for the month using the output for the multiple regression that you created in Requirement 2.
4. Between the simple linear regression and the multiple regression that you created for Requirements 1 and 2, which regression model is a better predictor of monthly occupancy costs? How do you know?

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1 Month 1 2 3 4 2 WN 3 456 7 8 9 10 11 5 6 7 8 9 10 B Year 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 Room nights sold 11,000 10,753 11,371 10,258 9,764 10,011 10,382 10,382 10,629 10,629 Average monthly high temperature 70 71 76 83 90 89 92 88 88 82 $ $ $ $ sssss $ $ $ $ 555 $ $ E Occupancy costs 381,545 376,164 385,899 359,028 345,129 354,259 361,837 366,991 374,560 372,709