Maria's Custom Cake Creations is a specialty bakery that produces artisan cakes for special events, such...

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Maria's Custom Cake Creations is a specialty bakery that produces artisan cakes for special events, such as weddings, birthdays, and corporate functions. The company produces cakes in three locations: New York, Los Angeles, and Las Vegas. Maria has operated the Los Angeles bakery for the past 20 years. Her niece, Angela, lives in Manhattan and, after spending a year training with Mara, opened up the New York bakery 5 years ago. The Las Vegas bakery was opened a year ago by one of Maria's most loyal customers, Brian, who graduated culinary school in the top of his class and worked as a pastry chef at a famous Michelin Star restaurant. Unfortunately, rising operating costs (wages, raw materials, rent, utilities, etc.) have put a strain of the company's cashflow and Maria can no longer afford to keep all three bakery locations open. Maria finds herself in the unenviable position of having to decide which location to close. To help her make this decision, she calculated the descriptive statistics for each bakery location. New York Revenue Los Angeles Las Vegas Revenue Revenue (000's) (000's) (000's) Mean 8.04 50.70 26.22 Standard Error 0.06 0.32 0.84 Median 8.0 50.5 3.0 Mode 7.4 46.0 1.0 Standard Deviation 1.98 10.14 68.35 Sample Variance 3.93 102.83 467.32 Kurtosis -0.22 -0.25 30.75 Skewness 0.01 -0.06 4.99 Range 12.6 60.0 726.0 Minimum 1.6 1.9 1.0 Maximum 14.2 79.0 727.0 Sum Count 844 84 5070 1000 1719 54 1. What are the advantages of using descriptive statistics to compare the three bakery locations? 2. What are the disadvantages of using descriptive statistics to compare the three bakery locations? 3. Maria believes that she can make her decision solely by comparing the mean revenue of the bakery locations. What are the risks of relying solely on the mean? 4. Compare the mean, median, and mode of each bakery location. What do the differences in the mean, median, and mode tell you about the revenue generated at each location? 5. What does the skewness tell you about the shape of the distribution of the data for each location? 6. Which location produces the least revenue? 7. Which location produces the least consistent revenue? Why might that be the case? 8. What additional information would be beneficial to make this decision? 9. Which bakery location should Maria close? Why? Maria's Custom Cake Creations is a specialty bakery that produces artisan cakes for special events, such as weddings, birthdays, and corporate functions. The company produces cakes in three locations: New York, Los Angeles, and Las Vegas. Maria has operated the Los Angeles bakery for the past 20 years. Her niece, Angela, lives in Manhattan and, after spending a year training with Mara, opened up the New York bakery 5 years ago. The Las Vegas bakery was opened a year ago by one of Maria's most loyal customers, Brian, who graduated culinary school in the top of his class and worked as a pastry chef at a famous Michelin Star restaurant. Unfortunately, rising operating costs (wages, raw materials, rent, utilities, etc.) have put a strain of the company's cashflow and Maria can no longer afford to keep all three bakery locations open. Maria finds herself in the unenviable position of having to decide which location to close. To help her make this decision, she calculated the descriptive statistics for each bakery location. New York Revenue Los Angeles Las Vegas Revenue Revenue (000's) (000's) (000's) Mean 8.04 50.70 26.22 Standard Error 0.06 0.32 0.84 Median 8.0 50.5 3.0 Mode 7.4 46.0 1.0 Standard Deviation 1.98 10.14 68.35 Sample Variance 3.93 102.83 467.32 Kurtosis -0.22 -0.25 30.75 Skewness 0.01 -0.06 4.99 Range 12.6 60.0 726.0 Minimum 1.6 1.9 1.0 Maximum 14.2 79.0 727.0 Sum Count 844 84 5070 1000 1719 54 1. What are the advantages of using descriptive statistics to compare the three bakery locations? 2. What are the disadvantages of using descriptive statistics to compare the three bakery locations? 3. Maria believes that she can make her decision solely by comparing the mean revenue of the bakery locations. What are the risks of relying solely on the mean? 4. Compare the mean, median, and mode of each bakery location. What do the differences in the mean, median, and mode tell you about the revenue generated at each location? 5. What does the skewness tell you about the shape of the distribution of the data for each location? 6. Which location produces the least revenue? 7. Which location produces the least consistent revenue? Why might that be the case? 8. What additional information would be beneficial to make this decision? 9. Which bakery location should Maria close? Why?