Owing to its wide applications in various fields, statistics is one of the most important disciplines. It helps researchers and scholars to understand and interpret information hidden behind the numbers. There are various forms of statistics but none helps in understanding data and coming up with viable deductions as descriptive statistics (Boslaugh, 2012). It helps to provide a link between the numbers and figures to create a description that can be understood by people from other fields. Descriptive statistics involves the assessment and display of data using different descriptive methods such as the measures of central tendencies and measures of dispersion (Bachman, 2004). In this paper, the aim is to understand the data provided in the case of Mi Casa restaurant with regard to customer loyalty and repeat business. The paper will achieve this through the calculation and interpretation of the relative frequencies of the type of clients and the reasons why they return to the restaurant from the locations at Downtown Phoenix.
Data Analysis and Explanation
Just like any other research process in statistics, data analysis and explanation is a crucial step in helping one to understand the information behind the numbers (Gupta & Walker, 2005). It is in light of this realization that table 1 shown below is presented to display the raw data that shows the frequency of types of customers and reason why the return to the restaurant.
Table 1: Data
Type of Client Frequency Reason for Returning Frequency
Work in Local Business 1216 Quality of Food 1064
Attending Sporting Event 874 Quality of Service 988
Live in Area 836 Meal Prices Fair 722
Attending Convention 456 Ability to Make Reservations 570
Vacationing in Area 233 Accommodate Large Groups 456
As pointed above, the table shows that there are different types of customers frequenting the restaurants. The customers have their own reasons for returning as shown in table 1. Figure 1 below is a graphical representation of the client analysis to ascertain the type of client coming to the restaurant and the reason for them returning to the restaurant. Based on the information that can be deduced from figure 1, it can be shown that customers working within the local business have a high frequency of returning compared to those in the vacationing area and any other category (Boslaugh, 2012). This category is closely followed by clients attending sporting events.
Figure 1: Type of Customer Analysis
Figure 2: Reason for Returning Analysis
In a similar fashion, figure 2 above shows that the frequency of the type of customers going to the restaurant is high when the quality of food at the hotel is high. It is also evident from the same figure 2 that the ability of the restaurant to accommodate large groups has little effect on the attendance (Bachman, 2004).
Pursuant to the above information on the analysis of the frequency, it can be concluded that the hotel can only achieve the highest number of client returns if it can maintain the quality of food. At the same time, the restaurant should channel its efforts to keep on attracting the customers working within the local business area as they are their most frequent customers based on their high possibility of returning compared to those in other categories.
Bachman, L. (2004). Statistical analyses for language assessment. Cambridge New York: Cambridge University Press.
Boslaugh, S. (2012). Statistics in a nutshell. Sebastopol, CA: O'Reilly Media.
Gupta, B. & Walker, H. (2005). Applied statistics for the Six Sigma Green Belt. Milwaukee: ASQ Press.
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