(1) The management of an international hotel chain is in the process of evaluating the possible...

      

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(1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis, the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel's average occupancy rate for the season. A sample of 14 existing hotels in the area is chosen, and each hotel reports its average occupancy rate. The management records the hotel's distance (in miles) from the beach. The following set of data is obtained: Distance (miles) 0.1 Occupancy (%) 92 0.1 0.2 0.3 0.4 0.4 0.5 0.6 0.7 95 96 90 89 96 90 83 85 Continue Distance (miles) 0.7 0.8 0.8 0.9 0.9 Occupancy (%) 80 78 76 72 75 A simple linear regression was ran with the occupancy rate as the dependent (explained) variable and distance from the beach as the independent (explaining) variable Оссрпс bo b (Distncy) 0. + COMPUTER OUTPUT – PART I INTERNATIONAL HOTEL REGRESSION FUNCTION & ANOVA FOR OCCPNCY OCCPNCY = 99.61444 - 26.703 DISTANCE R-Squared Adjusted R-Squared Standard error of estimate = 3.339362 = 0.848195 = 0.835545 Number of cases used = 14 Analysis of Variance p-value Sig Prob Regression 747.68 1 747.68390 67.04880 0.000002 Source SS df MS F Value Residual Total 133.82 12 11.15134 881.50 13 COMPUTER OUTPUT – PART 1 NTERNΑΤIONAL ΗOTEL REGRESSION COEFFICIENTS FOR OCCPNCY p-value Coefficient Std Error tValue Sig Prob 1.94107 51.31933 0.000000 Two-Sided Variable Constant 99.61444 DISTANCE -26.70300 3.26110 -8.18833 0.000002 * Standard error of estimate = 3.339362 Durbin-Watson statistic = 1.324282 %3D Use the above computer output to answer the following questions: (a) The simple linear regression model was: Occpne = he b (Distance) What is the estimated simple linear regression? ANSWER (b) What are the estimated values of b and b ANSWER b = ? b = ? (c) In the context of this problem, interpret the meaning behind the values you get for both coefficients b and bi. ANSWER (d) What sort of relationship exists between average hotel occupancy rate and the hotel's distance from the beach? Does this relationship make sense to you? Why or why not? ANSWER (e) Interpret the R-Square value in your computer output ANSWER (f) Predict the expected occupancy rate for a hotel that is (i) one mile from the beach in that area, (ii) one and half miles from the beach. ANSWER (g) In your mind, what other variables contribute positively or negatively to hotel occupancy besides distance from the beach? (1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis, the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel's average occupancy rate for the season. A sample of 14 existing hotels in the area is chosen, and each hotel reports its average occupancy rate. The management records the hotel's distance (in miles) from the beach. The following set of data is obtained: Distance (miles) 0.1 Occupancy (%) 92 0.1 0.2 0.3 0.4 0.4 0.5 0.6 0.7 95 96 90 89 96 90 83 85 Continue Distance (miles) 0.7 0.8 0.8 0.9 0.9 Occupancy (%) 80 78 76 72 75 A simple linear regression was ran with the occupancy rate as the dependent (explained) variable and distance from the beach as the independent (explaining) variable Оссрпс bo b (Distncy) 0. + COMPUTER OUTPUT – PART I INTERNATIONAL HOTEL REGRESSION FUNCTION & ANOVA FOR OCCPNCY OCCPNCY = 99.61444 - 26.703 DISTANCE R-Squared Adjusted R-Squared Standard error of estimate = 3.339362 = 0.848195 = 0.835545 Number of cases used = 14 Analysis of Variance p-value Sig Prob Regression 747.68 1 747.68390 67.04880 0.000002 Source SS df MS F Value Residual Total 133.82 12 11.15134 881.50 13 COMPUTER OUTPUT – PART 1 NTERNΑΤIONAL ΗOTEL REGRESSION COEFFICIENTS FOR OCCPNCY p-value Coefficient Std Error tValue Sig Prob 1.94107 51.31933 0.000000 Two-Sided Variable Constant 99.61444 DISTANCE -26.70300 3.26110 -8.18833 0.000002 * Standard error of estimate = 3.339362 Durbin-Watson statistic = 1.324282 %3D Use the above computer output to answer the following questions: (a) The simple linear regression model was: Occpne = he b (Distance) What is the estimated simple linear regression? ANSWER (b) What are the estimated values of b and b ANSWER b = ? b = ? (c) In the context of this problem, interpret the meaning behind the values you get for both coefficients b and bi. ANSWER (d) What sort of relationship exists between average hotel occupancy rate and the hotel's distance from the beach? Does this relationship make sense to you? Why or why not? ANSWER (e) Interpret the R-Square value in your computer output ANSWER (f) Predict the expected occupancy rate for a hotel that is (i) one mile from the beach in that area, (ii) one and half miles from the beach. ANSWER (g) In your mind, what other variables contribute positively or negatively to hotel occupancy besides distance from the beach?

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