Posted: September 18th, 2022

PLEASE REVIEW THE ATTACHMENT FOR REFERENCE TO THIS CURRENT ASSIGNMENT!!!!!! Review the Wk 2 – Apply: Statistical Report assignment. In preparation for writing your report to senior management next week, conduct the following descriptive statistics

Restaurant x
 

PLEASE REVIEW THE ATTACHMENT FOR REFERENCE TO THIS CURRENT ASSIGNMENT!!!!!!

Review the Wk 2 – Apply: Statistical Report assignment. 

In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Microsoft® Excel®. Answer the questions below in your Microsoft® Excel® sheet or in a separate Microsoft® Word document:

  • Insert a new column in the database that corresponds to “Annual Sales.” Annual Sales is the result of multiplying a restaurant’s “SqFt.” by “Sales/SqFt.”
  • Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables.
  • Create a box-plot for the “Annual Sales” variable. Does it look symmetric? Would you prefer the IQR instead of the standard deviation to describe this variable’s dispersion? Why?
  • Create a histogram for the “Sales/SqFt” variable. Is the distribution symmetric? If not, what is the skew? Are there any outliers? If so, which one(s)? What is the “SqFt” area of the outlier(s)? Is the outlier(s) smaller or larger than the average restaurant in the database? What can you conclude from this observation?
  • What measure of central tendency is more appropriate to describe “Sales/SqFt”? Why?
  •  

Pastas R Us, Inc.

Pastas R Us, Inc. 5

Pastas R Us, Inc.

David Leonard

University of Phoenix

DAT/565

May

7

, 2022

Scope and descriptive statistics

 Restaurant data analytics is the process of analyzing every data point related to a business and converting them into meaningful insights, which can help improve everything from menus and staff straining to restaurant policies and marketing campaigns. Larger restaurants may even have 8 or more technology vendors on their payroll, which highlights the need to invest in a reliable analytics solution. Restaurants that operate on this scale, think McDonalds scale, may be looking at big solutions to understand and make use of the huge amount of data they generate.

Objective

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

I. Understand whether the current expansion criteria can be improved.

II. evaluate the effectiveness of the Loyalty Card marketing strategy

III. identify feasible, actionable opportunities for improvement

The variables that were used in the 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

37.5

2500

7.03

#N/A

74

74

74

74

74

74

74

Column

1

Obs

SqFt

Sales/Person

Sales Growth%

LoyaltyCard%

Sales/SqFt

BachDeg%

Mean

37.5

2580.4

73

7.04

40

54054

7.4

14

0541

2.0

26

486

420.3054054

26.31081081

Standard Error

2.5

43.58345

0.034555901

0.7701093

0.064212

15.95377053

0.814285102

Median

2500

7

7.03

2.075

396.01

26.5

Mode

#N/A

4.05

2.04

29

Standard Deviation

21.50581

3

74

.919

0.29

72611

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

The total count of the data that were used in this case was 74 as indicated from the descriptive analysis table above. Most of the sizes of the restaurants are around 2580 square feet and the sales percentage growth mean is 7.4 while the mean for sales per person is 7.0. The mean for the company sales per square is 420.30.

Analysis

Scatter plot of BachDeg% versus Sales/SqFt

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). excluding outliers, we can see that the X axis increases as the Y axis increases. The sales per size of the restaurant increases as the BachDeg increases.

Scatter plot for Med Income versus Sales/SqFt

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). excluding outliers. However, the data are scattered at the center and there is no huge increase on the X axis. This means the med income the increases steadily against the sales per square

Scatter Plot

MedAge versus Sales/SqFt

In this case there is no relationship that exist.

LoyaltyCard (%) versus SalesGrowth (%)

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). excluding outliers

Recommendations and implementation

Based on the assessment above BachDeg% versus Sales/SqFt correlates and it is more effective. It shows that as the med income increases the size of the restaurant increases. Additionally, according to Scatter Plot MedAge versus Sales/SqFt, it shows that there is identified relationship between median age and the sales square per feet. It can be justified through use of line graph

The median age remains constant as the sales per square feet rise and fall which is a clear indication that there is no statistical relationship between the two. The loyalty card and the sales growth correlates.

Recommendations

The company should change the marketing strategy basing on % w/ Bachelor’s Degree (3 Miles) and the sales per square feet. Just like the loyalty card and the sales per square feet are correlated they should invest on the marketing strategies to increase the income of the restaurant

Instead of the company targeting the entire market they should focus on young people having the age of 35 years old. Since most of them having the age of 34 prefer having their services within the restaurant. The company implementing this strategy and committing their energy with this specific defined group with the market will help in improving their sales.

In a restaurant, collecting data is a bit easy as compared to other places. The most important thing to consider is identification cards. Identification may be a passport or a national identity card. Apart from acquiring the phone number and their address. Having this information will provide an endless opportunity for targeted marketing. 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.

References

Loeb, S., Dynarski, S., McFarland, D., Morris, P., Reardon, S., & Reber, S. (2017). Descriptive Analysis in Education: A Guide for Researchers. NCEE 2017-4023. 
National Center for Education Evaluation and Regional Assistance.

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

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

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