Crusty Dough Pizza Company Descriptive Statistics

Topics: Profit, Median, Arithmetic mean Pages: 5 (1222 words) Published: May 6, 2013
Crusty Dough Pizza Company – Maximizing Monthly Profits


This paper provides a summary of our analysis of the data obtained for 60 Crusty Dough Pizza Company restaurants. We compared 16 pizza store characteristics to monthly profit in order to determine the best indicators of success. The results of this analysis may be used to determine the store services and attributes that have the most bearing on profitably.

In our analysis, we compared the profits earned by 60 Crusty Dough Pizza Company restaurants to factors associated to their menu, amenities, services, and statistics regarding the restaurant communities. The factors that we analyzed are listed in Table 1.

Table 1. List of Factors Compared to Monthly Profit

We computed descriptive statistics (mean, median, mode, standard deviation, coefficient of variation, range, and outliers) for the 16 factors given in the data and for monthly profit. Of the 16 factors used in the analysis, five stand out for their clear association with an increase in monthly profits: 1) Monthly Advertising Expenditure, 2) Store Size, 3) Student Population, 4) Delivery Service, and 5) Customer Seating.

Table 2. Stores Ranked by Monthly Profit
For comparison purposes, we separated our stores into quartiles, and ranked them from highest to lowest, by profit. (Table 2) This method enabled us to demonstrate clear correlation between those stores that were most profitable and those that were least profitable in relation to the factors of monthly advertising, store size, and store population. (We noted that the coefficient of variation for the fourth quartile is extremely high, and that this data should be used with caution. We believe that at least part of this high variation is attributed to the fact that some stores did not make a profit, and actually lost revenue.)

For the factors of delivery service and customer seating, we separated stores that offered the service or amenity from those that did not, and compared them by monthly profit. This enabled us to demonstrate clear correlation between store profitably and whether or not the service or amenity was offered.

The following paragraphs summarize our analysis and explain our findings of correlation between key store factors and monthly profits.

Factor 1. Monthly Advertising Expenditures and Profit.

When analyzing the mean and median advertising expenditures of Crusty Dough Pizza stores, sorted by quartile, there appears to be a positive correlation between advertising expenditures and monthly profit. In general, stores that spend more on advertising earn more revenue. The data indicates a steep increase in profits for those stores that spend more money on advertising (Table 3.). The stores with the highest profit, on average, spend about twice as much on advertising as the stores that spend the least. This increase of approximately $1,000 in monthly expense translated, on average, to an increase in profit of more than $20,000 (see Table 2. comparing to top 25% to the bottom 25%). The calculated coefficient of variation (CV) for three of four quartiles, based on monthly advertising, were in a range of “good” for data consistency; the 3rd quartile was in the “fair” range. (Gardner, 2012)

Table 3. Store Profitability Compared by Monthly Advertising

Factor 2. Store Size and Profit.

In order to analyze the store size factor, we assigned numerical values to each of the four store sizes (Very Large – 4, Large – 3, Medium – 2, and Small – 1). We determined, through analysis of the mean and median values for store size, that size of store is a significant factor in determining store profitability. Overall, very large and large stores earn more profit than medium and small stores (Table 4.). The average size for the most profitable stores was 3.867 (more than large and slightly less than very large), while the average size of the least...

References: Gardner, E., Kimpel, T. and Zhao, T. (2012). “American Community Survey User Guide.” U.S. Office of Financial Management (OFM), May, 2012, Retrieved from:
Shafai, Jena. (2012). Business Resources, Bellevue University, MBA 610, chapter 3.
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