Eat Well Food Restaurants

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After, they calculated the mean, range and standard deviation of average monthly income from the sale of Food type A and Beverages type B and they found the following results (Figure 7).

Type A

Type B

MEAN

35187,8729

14837,76

STANDARD DIVIATION

11979,48626

4071,67

RANGE

61784,83333

21366,83

(Figure 7)

Then, they produced a histogram (Figure 8) for average monthly income derived from the sale of Food type A and Beverages type B to graphically display their distribution about the following table (Figure 9).

Type A

Type B

Total

35.188

14.838

(Figure 9)

[pic 10]

(Figure 8)

The above histogram shows the distributions between the averages for Type A food and Type B Beverages which means that the restaurant get a higher income from the sales of type A food compared to type B which is beverages. As displayed in the histogram, the difference is huge and income of beverages is almost half of the income from food. This was somehow expected, as beverages are cheaper than food and the customers rarely buy beverages enough to cover the expenses of the food.

In addition, they used the Privot table in order to investigate any possible association between two appropriate categorical variables. They selected Type A and Type B to investigate any association between them. They mentioned the averages of them and they ended up that the customers prefer more the food than the beverages, which means that the restaurant get a higher income from the sales of type A food compared to type B which is beverages. As the result of the beverages was less of the food. It seems in the bellow Privot table (Figure 10) and in the below histogram (Figure 11).

Values

Average of Type A

Average of Type B

422254,4747

178053,13

(Figure 10)

[pic 11]

(Figure 11)

On the other hand, there are a lot of competitors near the restaurant, fast food, so the monthly income will be affected negatively. Considering the fact that the amount of the restaurants that are close to this one, is big, so the clients have to choose between this and the others, having as a result that the monthly income will be affected.

Total monthly income

Distance

MIN

8.825

0,1

MAX

88.738

345

(Figure 12)

According to the above table (Figure 12), they could draw the conclusion that there is a big difference between the total monthly income when the distance of the restaurant is near from the nearest competitor the total monthly income affected positively and when the distance of the restaurant is close from the nearest competitors the total monthly income affected negatively.

[pic 12]

Finally, they found that there is a positive Correlation=1, but weak correlation between the average monthly income and the distance the restaurants are from competitors A positive correlation, when r is +1, it signifies that the two variables being compared have a perfect positive relationship.

CONCLUSION

To conclude, in this report the directors of the ‘Eat Well’ chain (a fast food restaurant chain), wanted to obtain a general profile of the restaurants. So, they collected all the data that they could find, through 100 randomly questionnaires. They used some tables and graphs, that manage to find the results, although they didn’t have all the questions answered. It has been proved that the distance from the ‘Eat Well’restaurant and all the other has affected the monthly income of the first. Also, it has been proved if the averages of food A or B have better quantity. According to the above, the directors of the ‘Eat Well’ chain found out how the results of these questions can help the improvement of their fast food restaurant chain and what should they change in their strategy.

APPENDIX

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