# Hotel Margin Regression Report

Please submit your EXCEL file with summary here – MUST BE DONE IN EXCEL – I have to show the teacher how I got the answers so please use formulas in excel or use a pivot table if needed
Location analysis is one function of operations management. Deciding where to locate a plant, warehouse, or retail outlet is a critical decision for any organization. A large number of variables must be considered in this decision problem. For example, a production facility must be located close to suppliers of raw resources and supplies, skilled labor and transportation to customers. Retail outlet must consider the type and number of potential customers. In the next example, we describe an application of regression analysis to find profitable locations for a motel chain.
La Quinata Motor Inns is a moderately priced chain of motor inns located across the United States. Its market is the frequent business traveler. The chain recently launched a campaign to increase market share by building new inns. The management of the chain is aware of the difficulty in choosing locations for new motels Moveover, making decisions without adequate information often results in poor decisions. Consequently, the chain’s management acquired data on 100 randomly selected inns belonging to La Quinta. The objects were to predict which sites are likely to be profitable.
To measure profitability, La Qinata used operation margin, which is the ratio of the sum of profit, depreciation and interest expenses divided by total revenue. (Although occupancy is often used as a measure of a motels success, the company statistician concluded that occupancy was too unstable, especially during economic turbulence.) The higher the operation margin, the greater the success of the inn. La Quinta defines profitable inns as those with a operating margin in excess of 50%. unprofitable inns are those with margins of less than 30%. After a discussion with a number of experienced managers, La Quinta decided to select one or two independent variables from each of the following categories, competition, market awareness, demand generators, demographics, and physical location. To measure the degree of competition, they determined the total number of motels and hotel rooms within 3 miles of each La Qunita inn. Market awareness was measured by the number of miles to the closest competing motel. Two variables that represent sources of customers were chosen. The amount of office space and college and university enrollment in the surrounding community are demand generators. Both of these are measures of economic activity. A demographic variable that describes the community is the median household income. Finally, as a measure of the physical qualities of the location La Quinta choose the distance to the downtown core. These data are stored using the following format
Colum 1: y = operating margin, in percent
Colum 2: x1 = Total number of motel and hotel rooms with 3 miles of La Quinta inn
Colum 3:X2 = Number of miles to closet competition
Colum 4: X3= office space in thousands of square feet in surrounding community
Colum 5: X4 = College and university enrollment (in thousands) in nearby university or college
Colum 6: X5 = median household income (in thousands) in surrounding community
colum 7 : X6= Distance (in miles) to the downtown core
Develop a regress analysis
b. Test to determine where there is enough evidence to infer that the model is valid
Test each of the slop coefficients
Interpret the coefficients
Predict with 95% confidence the operating margin of a site with the following characteristics
There are 3,815 rooms within 3 miles of the site, the closest other hotel or motel is 9 miles away, the amount of office space is 476,000 square fee , there is one college and one university with a total enrollment of 24,500 students, the median income in the area is \$35,000, and the distance to the downtown core is 11.2 miles.

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