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Concur Technologies, Inc., is a large expense-management company located in Redm

ID: 3309282 • Letter: C

Question

Concur Technologies, Inc., is a large expense-management company located in Redmond, Washington.  The Wall Street Journalasked Concur to examine the data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city, with an average daily hotel room rate of $198 and an average amount spent on entertainment, including group meals and tickets for shows, sports, and other events, of $172. In comparison, the U.S. averages for these two categories were $89 for the room rate and $99 for entertainment. The table in the Excel Online file below shows the average daily hotel room rate and the amount spent on entertainment for a random sample of 9 of the 25 most visited U.S. cities (The Wall Street Journal, August 18, 2011). Construct a spreadsheet to answer the following questions.

Hotel Room Rate ($)

152

97

87

112

93

100

133

90

81

Entertainment ($)

161

104

103

141

101

120

165

141

96

c. Develop the least squares estimated regression equation.

     (to 4 decimals)

d. Provide an interpretation for the slope of the estimated regression equation (to 3 decimals).

The slope of the estimated regression line is approximately________ . So, for every dollar increase in the hotel room rate the amount spent on entertainment increases by $_______.

e. The average room rate in Chicago is $128, considerably higher than the U.S. average. Predict the entertainment expense per day for Chicago (to whole number).

$ _______

Explanation / Answer

c)

y^ = 24.1903 + 0.9675 *x

where Y is entertainment

x is hotel rate

d) The slope of the estimated regression line is approximately 0.9675 . So, for every dollar increase in the hotel room rate the amount spent on entertainment increases by $ 0.9675

e) x = 128

y^ = 24.1903 + 0.9675 *128

= 148.0303

= 148

SUMMARY OUTPUT Regression Statistics Multiple R 0.844901599 R Square 0.713858712 Adjusted R Square 0.672981386 Standard Error 15.35721355 Observations 9 ANOVA df SS MS F Significance F Regression 1 4118.6475 4118.6475 17.46343923 0.00414278 Residual 7 1650.908056 235.8440079 Total 8 5769.555556 Coefficients Standard Error t Stat P-value Lower 95% Intercept 24.19027778 24.84260317 0.973741665 0.362624285 -34.55314416 hotel rate 0.9675 0.231518705 4.178928 0.00414278 0.420045255
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