Sarah McVea_quiz5.xlsx - This quiz has the same context as the previous one Note however that the data(and hence the rergression results from this quiz

# Sarah McVea_quiz5.xlsx - This quiz has the same context as...

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FOR ALL QUESTIONS, YOU SHOULD SHOW THE DETAILS OF YOUR WORK. This quiz has the same context as the previous one. Note, however, that the data (and hence the rergression results) from this quiz are different than in the previous one. A US hotel chain is considering ways to enter the European market. Before doing so, they ask an analyst to study characteristics of current European hotels. The analyst randomly samples 60 hotels from a popular travel website and also uses the site to capture data on several hotel characteristics. The variables he investigated and their values for the sampled hotels are found in the Hotel Data sheet. (The first row contains the names of the variables. Note that the first column is just a label or identifier for each hotel.) Ultimately the analyst hopes to identify the drivers of hotel ratings, but he also wants to explore some of the characteristics of the population of hotels from which he has sampled. For an interesting article on ratings, see ? nl=todaysheadlines&emc=edit_th_20131209&_r=0. 1. The data on the Hotel Data sheet have been coded to be ready to run a regression. For the qualitative factors that have yes/no values, 'No' was coded as the base case. For the star rating, 3 Star was used as the base case. Use the data to create a multiple regression model to explain rating as a function of the other variables. All other things being equal, what do you predict the difference in rating will be between a 5 Star hotel and a 3 Star hotel? Put your point estimate of the difference in cell B3 of the Answer Summary Sheet. If you estimate the rating will be higher for a 5 Star hotel, enter a positive number; otherwise enter a negative number. In cell C3 of the Answer Summary Sheet, put the lower end of a 95% confidence interval estimate of the difference; in cell D3 put the upper end of the 95% confidence interval estimate.

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