Statistical Report

RUNNING Head: Restaurant chain

Pastas R Us, Inc. 9

Restaurant chain

Jason Parkhill

DAT/565

April 12, 2021

Scope and descriptive statistics

Data analytics is a systematic process of making analysis of the data sets which have a relationship between the business operations and changing them into knowledge that can be used to make a business decision. In the Pasta R Us case the knowledge gained from the data analysis will be used in the improvement of the restaurant policies, menu, staff training and the marketing campaigns. In larger restaurant like the Pasta, may have more than 10 vendors on their payroll, which gives a reason to make an investment on a reliable analytics solution. Most of restaurants implement the analytic tools to seek for solutions to understand and make use of the big data to gain knowledge.

Objective

The main objective of this research is to undertake data analysis in order to:

I. Comprehend if the current expansion criteria can be upgraded.

II. Make an evaluation of the effectiveness of the Loyalty Card marketing strategy which was recently introduced.

III. Make an identification of the feasible, actionable opportunities that require improvement.

Various variables were used in this case to come up with the descriptive analysis. Variables that used in this analysis include the size of the restaurant in square feet, the average spending of an individual in a restaurant, the sales growth over the previous years, the loyalty card percentage of the net sales, annual sales per sq. ft., median income and median age.

The descriptive analysis

Column1	Obs	SqFt	Sales/Person	Sales Growth%	LoyaltyCard%	Sales/SqFt	BachDeg%
Mean	37.5	2580.473	7.044054054	7.4140541	2.026486	420.3054054	26.31081081
Standard Error	2.5	43.58345	0.034555901	0.7701093	0.064212	15.95377053	0.814285102
Median	37.5	2500	7	7.03	2.075	396.01	26.5
Mode	#N/A	2500	7.03	4.05	2.04	#N/A	29
Standard Deviation	21.50581	374.919	0.2972611	6.6247303	0.552371	137.2395233	7.004745311
Sample Variance	462.5	140564.3	0.088364161	43.887052	0.305114	18834.68676	49.06645687
Kurtosis	-1.2	3.760921	0.85439895	1.146166	1.4536	2.880513142	-0.937297935
Skewness	1E-16	0.527171	0.903631503	0.4937475	-0.756891	1.23589655	0.140544196
Range	73	2548	1.43	37.12	3.09	808.56	26
Minimum	1	1251	6.54	-8.31	0.29	178.56	14
Maximum	74	3799	7.97	28.81	3.38	987.12	40
Sum	2775	190955	521.26	548.64	149.96	31102.6	1947
Count	74	74	74	74	74	74	74

The total number of the samples that were used for analysis is 74. The average square feet the descriptive analysis conducted from the above table indicates that majority of the restaurants’ sizes are 2580 square feet. Additionally, the sales percentage growth average is 7.4 on the other side the average sales per person is 7.0 and the average company sales per square is 420.

Analysis

Scatter plot of BachDeg% versus Sales/SqFt

BachDeg/sales/Square feet relationship is a positive relationship because as the X-values move to the right, which is an indication of an increase, the Y-values on the other side moves up, increases. The data portrays a positive relationship which indicates that as the sales per size of the restaurant increases the BachDeg increases.

Scatter plot for Med Income versus Sales/SqFt

Again, in this case the relationship shown by the scatter plot indicates that there is a positive relationship between the variables as the Med Income increases the sales per square feet increases. The type of relationship that exist in this case is a positive relationship. This is because As the X-values increase (move right), the Y-values tend to increase (move up).in this case the plot are concentrated at the center. This concertation creates a small increase on the X-axis that is why we conclude that med income increases steadily against the sales per square.

Scatter Plot MedAge versus Sales/SqFt

There is no relationship that exist in this case. From the observation the data points portray no significant increase both in the X-axis and the Y axis.

LoyaltyCard (%) versus Sales Growth (%)

Finally, in this case there is positive relationship since there is significant increase in the X-axis as the Y-axis increases.

Recommendations and implementation

According to the evaluation carried out, it is clear that BachDeg% and Sales/SqFt correlates and it is more efficient when it is used by the company to make the required adjustment in order to improve their daily operation. Additionally, considering the scatter plot of the MedAge versus Sales/SqFt, there is a no relationship between the age and the sales per square feet. Additionally, we can implement the line graph to identify if there is an existing relationship.

MedAge versus Sales/SqFt

From the representation of the line graph above, there is no significant relationship between the sales per square feet and the median age. The median age is constant throughout while the sales square feet rise and fall meaning the median age does not affect the sales per square feet. Finally, there a positive relationship between the loyalties card which was introduced and the sales growth.

Recommendations

According to the descriptive analysis above the company should change and improve some of the strategies in order to increase their income. Majorly they should consider the marketing strategy based on bachelor’s degrees (3 miles) and the sales per square feet. Besides targeting the entire market, the company should be specifically concentrating on the younger people aging less than 35 years old. Majority of people aging 34 years old prefer being served within the restaurants.

The process of collecting data in a restaurant involve collecting is not complicated compared to other institutions. Collection of data can be fetched from the identification cards which includes passports and national identification card. Apart from fetching information from the identification cards, the data can be fetched from the address, phone number provided by the customers when reporting in. Some of the POS systems allows the restaurant to access the demographic data of their customers and if they find missing data, they can be filled using the public records. Collection and storage of this data will provide an endless information for segmentation in their market.

References

Kadim, A., & Sunardi, N. (2019, May). Eviews Analysis; Determinan Tourism, Restaurant and Hotel Company's Soundness and Performance. In Proceeding Interuniversity Forum for Strengthening Academic Competency (Vol. 1, No. 1, pp. 332-340).

Liu, P., & Tse, E. C. Y. (2018). Exploring factors on customers’ restaurant choice: an analysis of restaurant attributes. British Food Journal.

Mavridou, A. M., Bergmans, L., Barendregt, D., & Lambrechts, P. (2017). Descriptive analysis of factors associated with external cervical resorption. Journal of endodontics, 43(10), 1602-1610.

LoyaltyCard(%) versus SalesGrowth(%)

LoyaltyCard% -8.31 -4.01 -3.94 -3.39 -3.3 -1.94 -0.77 -0.37 -0.25 -0.17 0.47 0.55000000000000004 0.77 1.92 2.0499999999999998 2.12 2.84 2.88 3.96 4.04 4.05 4.05 4.24 4.58 5.09 5.14 5.48 5.86 5.91 5.98 6.08 6.08 6.13 6.27 6.57 6.9 6.94 7.12 7.39 7.67 7.91 8.08 8.27 8.5399999999999991 8.58 8.7200000000000006 8.75 8.7899999999999991 8.9 9.1199999999999992 9.4700000000000006 10.17 10.66 10.97 11.34 11.45 11.51 11.73 11.83 11.95 12.47 12.8 13.78 14.09 14.23 14.6 14.88 15.42 16.18 17.23 18.43 20.76 25.54 28.81 2.0699999999999998 2.54 1.66 2.06 2.48 2.96 2.2799999999999998 2.34 2.2000000000000002 2.34 2.09 2.4700000000000002 2.04 2.02 2.0099999999999998 2.64 2.2200000000000002 2.0699999999999998 1.94 2.17 0.72 2 1.81 2.13 2.5 2.63 1.95 2.04 1.41 2.0499999999999998 2.13 2.08 2.73 1.95 2.04 1.62 1.95 1.64 1.78 2.23 2.15 2.83 2.37 3.07 2.19 1.28 1.76 2.5099999999999998 1.9 1.98 2.41 2.17 2.16 0.28999999999999998 1.85 1.88 2.19 2.56 2.16 2.1 1.98 0.87 1.07 3.38 1.17 2.14 0.93 2.2200000000000002 1.68 2.41 2.81 1.0900000000000001 0.64 1.77

MedAge versus Sales/SqFt

Sales/SqFt 701.97 209.93 364.92 443.04 399.2 264.64 571.59 642.25 461.45 638.82000000000005 484.38 581.09 267.70999999999998 572.84 586.48 368.73 351.47 458.24 987.12 357.45 405.77 680.8 368.02 303.95 393.9 562.12 494.88 310.07 373.46 235.81 413.08 625.22 274.3 542.62 178.56 375.33 329.09 297.37 323.17 468.84 352.57 380.34 398.12 312.14999999999998 452.16 698.64 367.19 431.93 367.06 400.53 414.36 481.11 538.05999999999995 330.48 249.93 291.87 517.4 551.58000000000004 386.81 427.5 453.94 512.46 345.27 234.04 348.33 348.47 294.95 361.14 467.71 403.78 245.74 339.94 400.82 326.54000000000002 MedAge 34.4 41.2 40.299999999999997 35.4 31.5 36.299999999999997 35.1 37.6 34.9 34.799999999999997 36.200000000000003 32.200000000000003 30.9 37.700000000000003 34.299999999999997 32.4 32.1 31.4 30.4 33.9 35.6 35.9 33.6 37.9 40.6 37.700000000000003 36.4 40.9 35 26.4 37.1 30.3 31.3 29.6 32.9 40.700000000000003 29.3 37.299999999999997 39.799999999999997 33.9 35 35 35.9 33 30.9 38.5 40.5 32.1 34.799999999999997 38 37 34.700000000000003 36.4 36.799999999999997 32.200000000000003 34.799999999999997 36.700000000000003 33.799999999999997 34.200000000000003 39 34.9 39.299999999999997 35.6 36 41.1 24.7 40.5 32.9 30.3 36.200000000000003 32.4 43.5 41.6 31.4

BachDeg/Sales/SqFt

Sales/SqFt 31 20 24 29 18 30 14 33 28 29 39 23 22 37 24 17 37 22 36 34 26 20 20 26 21 37 34 34 30 16 28 36 18 36 18 24 22 29 25 28 40 39 30 17 22 29 19 29 18 19 34 25 30 21 30 30 28 31 16 31 40 33 28 23 16 25 25 18 15 19 27 21 29 15 701.97 209.93 364.92 443.04 399.2 264.64 571.59 642.25 461.45 638.82000000000005 484.38 581.09 267.70999999999998 572.84 586.48 368.73 351.47 458.24 987.12 357.45 405.77 680.8 368.02 303.95 393.9 562.12 494.88 310.07 373.46 235.81 413.08 625.22 274.3 542.62 178.56 375.33 329.09 297.37 323.17 468.84 352.57 380.34 398.12 312.14999999999998 452.16 698.64 367.19 431.93 367.06 400.53 414.36 481.11 538.05999999999995 330.48 249.93 291.87 517.4 551.58000000000004 386.81 427.5 453.94 512.46 345.27 234.04 348.33 348.47 294.95 361.14 467.71 403.78 245.74 339.94 400.82 326.54000000000002

MedIncome/sales/SqFt

MedIncome 701.97 209.93 364.92 443.04 399.2 264.64 571.59 642.25 461.45 638.82000000000005 484.38 581.09 267.70999999999998 572.84 586.48 368.73 351.47 458.24 987.12 357.45 405.77 680.8 368.02 303.95 393.9 562.12 494.88 310.07 373.46 235.81 413.08 625.22 274.3 542.62 178.56 375.33 329.09 297.37 323.17 468.84 352.57 380.34 398.12 312.14999999999998 452.16 698.64 367.19 431.93 367.06 400.53 414.36 481.11 538.05999999999995 330.48 249.93 291.87 517.4 551.58000000000004 386.81 427.5 453.94 512.46 345.27 234.04 348.33 348.47 294.95 361.14 467.71 403.78 245.74 339.94 400.82 326.54000000000002 45177 51888 51379 66081 50999 41562 44196 50975 72808 79070 78497 41245 33003 90988 37950 45206 79312 37345 46226 70024 54982 54932 34097 46593 51893 88162 89016 114353 75366 48163 49956 45990 45723 43800 68711 65150 39329 63657 67099 75151 93876 79701 77115 52766 32929 87863 73752 85366 39180 56077 77449 56822 80470 55584 78001 75307 76375 61857 61312 72040 92414 92602 59599 72453 67925 42631 75652 39650 48033 67403 80597 60928 73762 64225

MedAge versus Sales/SqFt

MedAge 701.97 209.93 364.92 443.04 399.2 264.64 571.59 642.25 461.45 638.82000000000005 484.38 581.09 267.70999999999998 572.84 586.48 368.73 351.47 458.24 987.12 357.45 405.77 680.8 368.02 303.95 393.9 562.12 494.88 310.07 373.46 235.81 413.08 625.22 274.3 542.62 178.56 375.33 329.09 297.37 323.17 468.84 352.57 380.34 398.12 312.14999999999998 452.16 698.64 367.19 431.93 367.06 400.53 414.36 481.11 538.05999999999995 330.48 249.93 291.87 517.4 551.58000000000004 386.81 427.5 453.94 512.46 345.27 234.04 348.33 348.47 294.95 361.14 467.71 403.78 245.74 339.94 400.82 326.54000000000002 34.4 41.2 40.299999999999997 35.4 31.5 36.299999999999997 35.1 37.6 34.9 34.799999999999997 36.200000000000003 32.200000000000003 30.9 37.700000000000003 34.299999999999997 32.4 32.1 31.4 30.4 33.9 35.6 35.9 33.6 37.9 40.6 37.700000000000003 36.4 40.9 35 26.4 37.1 30 .3 31.3 29.6 32.9 40.700000000000003 29.3 37.299999999999997 39.799999999999997 33.9 35 35 35.9 33 30.9 38.5 40.5 32.1 34.799999999999997 38 37 34.700000000000003 36.4 36.799999999999997 32.200000000000003 34.799999999999997 36.700000000000003 33.799999999999997 34.200000000000003 39 34.9 39.299999999999997 35.6 36 41.1 24.7 40.5 32.9 30.3 36.200000000000003 32.4 43.5 41.6 31.4