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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION

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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε,where Y is the hotel occupancy rate,X1 is the total number of passengers arriving at the airport,X2 is a price index of local hotel room rates,X3 is the consumer confidence index,and X4 is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results: THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 67.1 + 0.02x1 - 0.055x2 + 0.08x3 + 12.3x4,R2 = 0.67, THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 58.3, THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 0.008, THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 0.01, THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 0.06, THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board,you are interested in determining the factors that influence the hotel occupancy rate in your city each month.Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers.You develop the following model: Y = β<sub>0</sub> + β<sub>1</sub>X<sub>1</sub> + β<sub>2</sub>X<sub>2</sub> + β<sub>3</sub>X<sub>3</sub> + β<sub>4</sub>X<sub>4</sub> + ε,where Y is the hotel occupancy rate,X<sub>1</sub> is the total number of passengers arriving at the airport,X<sub>2</sub> is a price index of local hotel room rates,X<sub>3</sub> is the consumer confidence index,and X<sub>4</sub> is a dummy variable = 1 during the months of June,July,and August.You look at data from the past 36 months and obtain the following results:    = 67.1 + 0.02x<sub>1</sub> - 0.055x<sub>2</sub> + 0.08x<sub>3</sub> + 12.3x<sub>4</sub>,R<sup>2</sup> = 0.67,    = 58.3,    = 0.008,    = 0.01,    = 0.06,    = 4.7,and SSE = 576. -Test the hypothesis H<sub>0</sub> : β<sub>2</sub> = 0 and interpret your results.
= 4.7,and SSE = 576.
-Test the hypothesis H0 : β2 = 0 and interpret your results.


Definitions:

Accounts Receivable Turnover

A financial ratio that measures how efficiently a company collects cash from credit sales by comparing net credit sales with the average accounts receivable balance.

Net Credit Sales

The total amount of sales made on credit, subtracting returns and allowances.

Accounts Receivable

Money owed to a company by its customers for goods or services that have been delivered or used but not yet paid for.

Times Interest Earned Ratio

The times interest earned ratio is a financial metric that measures a company's ability to meet its debt obligations based on its current earnings before interest and taxes (EBIT).

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