purposeofassignment.xlsx

ChartDataSheet_

This worksheet contains values required for MegaStat charts.

Residuals X data 3/19/2007 7:49.25

66 18 45177 34.4 31

69 16 51888 41.2 20

67 10 51379 40.3 24

70 4 66081 35.4 29

78 0 50999 31.5 18

62 28 41562 36.3 30

70 28 44196 35.1 14

84 29 50975 37.6 33

68 22 72808 34.9 28

60 42 79070 34.8 29

80 36 78497 36.2 39

64 32 41245 32.2 23

80 22 33003 30.9 22

88 78 90988 37.7 37

42 35 37950 34.3 24

68 32 45206 32.4 17

80 48 79312 32.1 37

84 32 37345 31.4 22

35 27 46226 30.4 36

84 24 70024 33.9 34

78 16 54982 35.6 26

80 39 54932 35.9 20

70 70 34097 33.6 20

76 33 46593 37.9 26

56 12 51893 40.6 21

65 32 88162 37.7 37

62 0 89016 36.4 34

66 20 114353 40.9 34

76 24 75366 35 30

92 36 48163 26.4 16

112 34 49956 37.1 28

66 15 45990 30.3 36

70 28 45723 31.3 18

60 15 43800 29.6 36

86 10 68711 32.9 18

76 0 65150 40.7 24

68 16 39329 29.3 22

64 0 63657 37.3 29

52 36 67099 39.8 25

78 26 75151 33.9 28

64 28 93876 35 40

82 32 79701 35 39

86 30 77115 35.9 30

92 16 52766 33 17

72 10 32929 30.9 22

90 24 87863 38.5 29

64 20 73752 40.5 19

80 20 85366 32.1 29

102 30 39180 34.8 18

70 26 56077 38 19

62 26 77449 37 34

68 20 56822 34.7 25

74 24 80470 36.4 30

84 14 55584 36.8 21

70 32 78001 32.2 30

96 32 75307 34.8 30

70 22 76375 36.7 28

76 32 61857 33.8 31

62 28 61312 34.2 16

92 23 72040 39 31

60 20 92414 34.9 40

54 15 92602 39.3 33

110 23 59599 35.6 28

78 0 72453 36 23

72 31 67925 41.1 16

74 29 42631 24.7 25

94 0 75652 40.5 25

80 16 39650 32.9 18

124 0 48033 30.3 15

46 20 67403 36.2 19

66 0 80597 32.4 27

63 28 60928 43.5 21

72 15 73762 41.6 29

76 24 64225 31.4 15

NormalPlot data 3/19/2007 7:49.03

-259.9497306439 -2.3669115357

-188.5900144767 -2.0061237235

-178.1863109741 -1.8007082352

-165.2888689211 -1.6514108613

-156.2930386781 -1.5318456091

-147.1995334043 -1.4308738679

-145.0204151759 -1.3426905457

-132.7962270775 -1.2638662791

-132.5838765031 -1.1921973902

-127.8657575015 -1.1261791757

-124.4916500844 -1.0647357757

-123.016384493 -1.0070695657

-118.431306853 -0.952571595

-110.8440652315 -0.9007655189

-110.1477551652 -0.8512709934

-109.3430277914 -0.8037789242

-105.1097263145 -0.7580342264

-104.7616892077 -0.7138235056

-100.1917272772 -0.6709660579

-96.9455399284 -0.6293071641

-78.5222407532 -0.588713006

-66.833182556 -0.5490667518

-63.9367962151 -0.5102654979

-54.9666697606 -0.4722178495

-49.5089341383 -0.4348419815

-43.817663257 -0.3980640685

-30.5622414309 -0.3618169976

-29.7056802184 -0.3260393031

-28.8211160258 -0.2906742745

-21.3829190469 -0.2556692022

-20.8096302471 -0.220974732

-18.0336858908 -0.1865443062

-16.4732294274 -0.152333674

-15.5268611118 -0.1183004556

-12.5832024808 -0.0844037498

-11.5991899485 -0.0506037738

-10.6416197419 -0.0168615273

-6.4663288735 0.0168615273

6.6082090726 0.0506037738

10.1026389027 0.0844037498

10.1556691582 0.1183004556

11.5424324103 0.152333674

13.4792557233 0.1865443062

15.0213966843 0.220974732

18.9663798116 0.2556692022

19.2122025279 0.2906742745

19.5938287738 0.3260393031

19.7419844304 0.3618169976

23.7470781354 0.3980640685

25.1736217387 0.4348419815

28.9194386872 0.4722178495

38.4697564504 0.5102654979

50.9831788417 0.5490667518

53.0357068283 0.588713006

61.102903906 0.6293071641

63.1204953548 0.6709660579

63.8380153718 0.7138235056

71.0833539728 0.7580342264

71.3281648375 0.8037789242

75.1828858929 0.8512709934

75.2802525469 0.9007655189

81.3206554357 0.952571595

81.6351025536 1.0070695657

105.576464442 1.0647357757

115.0253844293 1.1261791757

122.2233804168 1.1921973902

150.1178490106 1.2638662791

180.3934285167 1.3426905457

196.2671375845 1.4308738679

205.7993140008 1.5318456091

234.8563337617 1.6514108613

289.7338930992 1.8007082352

336.0904495556 2.0061237235

372.5195939607 2.3669115357

Residuals X data 3/19/2007 8:01.41

66 18 45177 34.4 31

69 16 51888 41.2 20

67 10 51379 40.3 24

70 4 66081 35.4 29

78 0 50999 31.5 18

62 28 41562 36.3 30

70 28 44196 35.1 14

84 29 50975 37.6 33

68 22 72808 34.9 28

60 42 79070 34.8 29

80 36 78497 36.2 39

64 32 41245 32.2 23

80 22 33003 30.9 22

88 78 90988 37.7 37

42 35 37950 34.3 24

68 32 45206 32.4 17

80 48 79312 32.1 37

84 32 37345 31.4 22

35 27 46226 30.4 36

84 24 70024 33.9 34

78 16 54982 35.6 26

80 39 54932 35.9 20

70 70 34097 33.6 20

76 33 46593 37.9 26

56 12 51893 40.6 21

65 32 88162 37.7 37

62 0 89016 36.4 34

66 20 114353 40.9 34

76 24 75366 35 30

92 36 48163 26.4 16

112 34 49956 37.1 28

66 15 45990 30.3 36

70 28 45723 31.3 18

60 15 43800 29.6 36

86 10 68711 32.9 18

76 0 65150 40.7 24

68 16 39329 29.3 22

64 0 63657 37.3 29

52 36 67099 39.8 25

78 26 75151 33.9 28

64 28 93876 35 40

82 32 79701 35 39

86 30 77115 35.9 30

92 16 52766 33 17

72 10 32929 30.9 22

90 24 87863 38.5 29

64 20 73752 40.5 19

80 20 85366 32.1 29

102 30 39180 34.8 18

70 26 56077 38 19

62 26 77449 37 34

68 20 56822 34.7 25

74 24 80470 36.4 30

84 14 55584 36.8 21

70 32 78001 32.2 30

96 32 75307 34.8 30

70 22 76375 36.7 28

76 32 61857 33.8 31

62 28 61312 34.2 16

92 23 72040 39 31

60 20 92414 34.9 40

54 15 92602 39.3 33

110 23 59599 35.6 28

78 0 72453 36 23

72 31 67925 41.1 16

74 29 42631 24.7 25

94 0 75652 40.5 25

80 16 39650 32.9 18

124 0 48033 30.3 15

46 20 67403 36.2 19

66 0 80597 32.4 27

63 28 60928 43.5 21

72 15 73762 41.6 29

76 24 64225 31.4 15

NormalPlot data 3/19/2007 8:01.03

-259.9497306439 -2.3669115357

-188.5900144767 -2.0061237235

-178.1863109741 -1.8007082352

-165.2888689211 -1.6514108613

-156.2930386781 -1.5318456091

-147.1995334043 -1.4308738679

-145.0204151759 -1.3426905457

-132.7962270775 -1.2638662791

-132.5838765031 -1.1921973902

-127.8657575015 -1.1261791757

-124.4916500844 -1.0647357757

-123.016384493 -1.0070695657

-118.431306853 -0.952571595

-110.8440652315 -0.9007655189

-110.1477551652 -0.8512709934

-109.3430277914 -0.8037789242

-105.1097263145 -0.7580342264

-104.7616892077 -0.7138235056

-100.1917272772 -0.6709660579

-96.9455399284 -0.6293071641

-78.5222407532 -0.588713006

-66.833182556 -0.5490667518

-63.9367962151 -0.5102654979

-54.9666697606 -0.4722178495

-49.5089341383 -0.4348419815

-43.817663257 -0.3980640685

-30.5622414309 -0.3618169976

-29.7056802184 -0.3260393031

-28.8211160258 -0.2906742745

-21.3829190469 -0.2556692022

-20.8096302471 -0.220974732

-18.0336858908 -0.1865443062

-16.4732294274 -0.152333674

-15.5268611118 -0.1183004556

-12.5832024808 -0.0844037498

-11.5991899485 -0.0506037738

-10.6416197419 -0.0168615273

-6.4663288735 0.0168615273

6.6082090726 0.0506037738

10.1026389027 0.0844037498

10.1556691582 0.1183004556

11.5424324103 0.152333674

13.4792557233 0.1865443062

15.0213966843 0.220974732

18.9663798116 0.2556692022

19.2122025279 0.2906742745

19.5938287738 0.3260393031

19.7419844304 0.3618169976

23.7470781354 0.3980640685

25.1736217387 0.4348419815

28.9194386872 0.4722178495

38.4697564504 0.5102654979

50.9831788417 0.5490667518

53.0357068283 0.588713006

61.102903906 0.6293071641

63.1204953548 0.6709660579

63.8380153718 0.7138235056

71.0833539728 0.7580342264

71.3281648375 0.8037789242

75.1828858929 0.8512709934

75.2802525469 0.9007655189

81.3206554357 0.952571595

81.6351025536 1.0070695657

105.576464442 1.0647357757

115.0253844293 1.1261791757

122.2233804168 1.1921973902

150.1178490106 1.2638662791

180.3934285167 1.3426905457

196.2671375845 1.4308738679

205.7993140008 1.5318456091

234.8563337617 1.6514108613

289.7338930992 1.8007082352

336.0904495556 2.0061237235

372.5195939607 2.3669115357

Data

Pastas R Us, Inc. Database (n = 74 restaurants)

Square Feet Per Person Average Spending Sales Growth Over Previous Year (%) Loyalty Card % of Net Sales Annual Sales Per Sq Ft Median HH Income (3 Miles) Median Age (3 Miles) % w/ Bachelor’s Degree (3 Miles) Review the Wk 2 – Apply: Statistical Report assignment. 

Obs SqFt Sales/Person SalesGrowth% LoyaltyCard% Sales/SqFt MedIncome MedAge BachDeg% In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Excel®. Answer the questions below in your Excel sheet or in a separate Word document:

1 2354 6.81 -8.31 2.07 701.97 45177 34.4 31 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.”

2 2604 7.57 -4.01 2.54 209.93 51888 41.2 20 Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables.

3 2453 6.89 -3.94 1.66 364.92 51379 40.3 24 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?

4 2340 7.13 -3.39 2.06 443.04 66081 35.4 29 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?

5 2500 7.04 -3.30 2.48 399.20 50999 31.5 18 What measure of central tendency is more appropriate to describe “Sales/SqFt”? Why?

6 2806 6.93 -1.94 2.96 264.64 41562 36.3 30

7 2250 7.11 -0.77 2.28 571.59 44196 35.1 14

8 2400 7.13 -0.37 2.34 642.25 50975 37.6 33

9 2709 6.58 -0.25 2.20 461.45 72808 34.9 28

10 1990 6.77 -0.17 2.34 638.82 79070 34.8 29 Week 2

11 2392 6.66 0.47 2.09 484.38 78497 36.2 39 Purpose 

12 2408 7.03 0.55 2.47 581.09 41245 32.2 23 This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.

13 2627 7.03 0.77 2.04 267.71 33003 30.9 22

14 2500 7.00 1.92 2.02 572.84 90988 37.7 37 Scenario: 

15 1986 7.38 2.05 2.01 586.48 37950 34.3 24 Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:

16 2500 7.18 2.12 2.64 368.73 45206 32.4 17 Median age between 25 – 45 years old

17 2668 7.35 2.84 2.22 351.47 79312 32.1 37 Household median income above national average

18 2517 6.95 2.88 2.07 458.24 37345 31.4 22 At least 15% college educated adult population

19 1251 7.02 3.96 1.94 987.12 46226 30.4 36

20 2998 6.85 4.04 2.17 357.45 70024 33.9 34 Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.

21 2625 7.16 4.05 0.72 405.77 54982 35.6 26

22 2300 6.99 4.05 2.00 680.80 54932 35.9 20 The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.

23 2761 7.28 4.24 1.81 368.02 34097 33.6 20

24 2764 7.07 4.58 2.13 303.95 46593 37.9 26 Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.

25 2430 7.05 5.09 2.50 393.90 51893 40.6 21

26 2154 6.54 5.14 2.63 562.12 88162 37.7 37 Report:

27 2400 6.70 5.48 1.95 494.88 89016 36.4 34 Write a 750-word statistical report that includes the following sections:

28 2430 6.91 5.86 2.04 310.07 114353 40.9 34 Section 1: Scope and descriptive statistics

29 2549 7.58 5.91 1.41 373.46 75366 35.0 30 Section 2: Analysis

30 2500 7.03 5.98 2.05 235.81 48163 26.4 16 Section 3: Recommendations and Implementation

31 3653 6.84 6.08 2.13 413.08 49956 37.1 28

32 2440 6.94 6.08 2.08 625.22 45990 30.3 36 Section 1 – Scope and descriptive statistics

33 2600 7.07 6.13 2.73 274.30 45723 31.3 18 State the report’s objective.

34 2160 7.00 6.27 1.95 542.62 43800 29.6 36 Discuss the nature of the current database. What variables were analyzed?

35 2800 7.08 6.57 2.04 178.56 68711 32.9 18 Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.

36 2757 6.75 6.90 1.62 375.33 65150 40.7 24

37 2450 6.81 6.94 1.95 329.09 39329 29.3 22 Section 2 – Analysis 

38 2400 7.64 7.12 1.64 297.37 63657 37.3 29 Using Excel, create scatter plots and display the regression equations for the following pairs of variables:

39 2270 6.62 7.39 1.78 323.17 67099 39.8 25 “BachDeg%” versus “Sales/SqFt”

40 2800 6.76 7.67 2.23 468.84 75151 33.9 28 “MedIncome” versus “Sales/SqFt”

41 2520 7.11 7.91 2.15 352.57 93876 35.0 40 “MedAge” versus “Sales/SqFt”

42 2487 7.05 8.08 2.83 380.34 79701 35.0 39 “LoyaltyCard(%)” versus “SalesGrowth(%)”

43 2629 6.90 8.27 2.37 398.12 77115 35.9 30 In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.

44 3200 7.17 8.54 3.07 312.15 52766 33.0 17

45 2335 6.75 8.58 2.19 452.16 32929 30.9 22 Section 3: Recommendations and implementation

46 2500 7.45 8.72 1.28 698.64 87863 38.5 29 Based on your findings above, assess which expansion criteria seem to be more effective.Could any expansion criterion be changed or eliminated? If so, which one and why?

47 2449 7.00 8.75 1.76 367.19 73752 40.5 19 Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?

48 2625 6.96 8.79 2.51 431.93 85366 32.1 29 Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)

49 3150 7.30 8.90 1.90 367.06 39180 34.8 18 Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)

50 2625 6.96 9.12 1.98 400.53 56077 38.0 19

51 2741 6.71 9.47 2.41 414.36 77449 37.0 34 Cite references to support your assignment.

52 2500 6.82 10.17 2.17 481.11 56822 34.7 25

53 2450 6.58 10.66 2.16 538.06 80470 36.4 30 Format your citations according to APA guidelines.

54 2986 7.56 10.97 0.29 330.48 55584 36.8 21

55 2967 6.98 11.34 1.85 249.93 78001 32.2 30

56 3000 7.28 11.45 1.88 291.87 75307 34.8 30

57 2500 6.76 11.51 2.19 517.40 76375 36.7 28

58 2600 6.92 11.73 2.56 551.58 61857 33.8 31

59 2800 6.73 11.83 2.16 386.81 61312 34.2 16

60 2986 6.91 11.95 2.10 427.50 72040 39.0 31

61 2223 6.77 12.47 1.98 453.94 92414 34.9 40

62 2300 7.33 12.80 0.87 512.46 92602 39.3 33

63 3799 7.87 13.78 1.07 345.27 59599 35.6 28

64 2700 6.95 14.09 3.38 234.04 72453 36.0 23

65 2650 7.33 14.23 1.17 348.33 67925 41.1 16

66 2500 6.95 14.60 2.14 348.47 42631 24.7 25

67 2994 7.21 14.88 0.93 294.95 75652 40.5 25

68 2718 7.25 15.42 2.22 361.14 39650 32.9 18

69 3700 7.65 16.18 1.68 467.71 48033 30.3 15

70 2000 6.93 17.23 2.41 403.78 67403 36.2 19

71 2400 6.79 18.43 2.81 245.74 80597 32.4 27

72 2450 7.37 20.76 1.09 339.94 60928 43.5 21

73 2575 6.76 25.54 0.64 400.82 73762 41.6 29

74 2400 7.97 28.81 1.77 326.54 64225 31.4 15

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