Essays on Relationship between Annual Income and Restaurant Expenditure Report

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The paper "Relationship between Annual Income and Restaurant Expenditure" is a perfect example of a finance and accounting report.   This report is the result of an investigation on the customer characteristics who are likely to be customers in a fine, upscale restaurant with fine entré es, drinks, and desserts in a serene atmosphere. The study is done with full knowledge in restaurant operations and some knowledge in upscale restaurants but there is no surety that the city may require the need for such a restaurant. The major interest is establishing if there will be demand for the restaurant and the appropriate pricing.

In any market, there is likely to be a big difference in markets with regards to what consumer prefers and there income level (Daellenbach, 1994). The hypothesis of the study is There is a significant correlation between the income and what one spends in restaurants Methodology In this study, 50 respondents were randomly approached and were requested to fill in the questionnaire regarding the possibility of a restaurant being established in the area of investigation. 1. Obtaining two sets of 50 raw data pertaining to some business units. The respondents were asked to give the amount in dollars they spend on food and beverages in one sitting in a restaurant.

They were also asked to state their annual income in dollars. 2 Frequency distribution and histogram for the data using 7or 8 classes. Expenditure classes Class 1 < $2 Class2 $2-$4 Class3 $4.01-$6 Class4 $6.01-$8 Class5 $8.01-$10 Class6 $10.01-$12 Class 7 > $12     Annual income classes Class 1 < $10000 Class2 $10000-$19999 Class3 $20000-$29999 Class4 $30000-$39999 Class5 $40000-$49999 Class6 $50000-$59999 Class 7 $60000-$69999 Class 8 > $70000 Figure 1 Figure 2 3. Observation from the histogram about the data? From the histogram, it can be seen that the income data is much closer to normal distribution while the expenditure data is slightly skewed. 4. Using the data to find the descriptive measures of the data. Table 1 Column1     Mean 3.24 Standard Error 0.238293251 Median 3 Mode 2 Standard Deviation 1.684987737 Sample Variance 2.839183673 Kurtosis 0.731597038 Skewness 1.418165644 Range 5 Minimum 2 Maximum 7 Sum 162 Count 50  


Belton, V. (1990). Multiple Criteria Decision Analysis: Practically the only way to choose, in LC Hendry and RW Eglese (Eds), Operational Research Tutorial Papers, Operational Research Society, Birmingham.

Daellenbach, H. G. (1994). Systems and Decision Making, Wiley, Chichester,

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