As a?sales manager, you will?use statistical methods to support actionable business decisions?for Pastas R Us, Inc., a fast-casual restaurant chain specializing in noodl
As a sales manager, you will use statistical methods to support actionable business decisions for Pastas R Us, Inc., a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. In simpler terms, you are reviewing available information to determine if what your company is doing works. In this assessment, you use predictive and qualitative analysis skills to create a report for the executive team from available Pastas R Us, Inc. data about the effectiveness of the current expansion criteria, loyalty card program, and marketing position.
Scenario
Since its inception, the Pastas R Us business development team has favored opening new restaurants in areas that satisfy the following demographic conditions within a 3-mile radius:
Median age is between 25–45 years old.
Household median income is above the national average.
At least 15% of the adult population is college educated.
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.
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 1,200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.
Preparation
Analyze the Pastas R Us charts file for your report, including the scatter plots and regression equations for the following pairs of variables:
“Sales/Sq.Ft. ($)” versus “Bach. Degrees (%)”
“Median Income ($)” versus “Sales/Sq.Ft. ($)”
“Median Age (Years)” versus “Sales/Sq.Ft. ($)”
“Loyalty Card (%)” versus “Sales Growth (%)”
Assessment Deliverable
Write a 700- to 1,050-word predictive and qualitative analysis report of Pastas R Us, Inc. that includes the following sections: scope and descriptive statistics, analysis, and recommendations and implementation.
Section 1: Scope and descriptive statistics
State the report’s objective.
Discuss the nature of the current data. What variables were analyzed?
Summarize your descriptive statistical findings from Week 1.
Section 2: Analysis
Interpret the scatter plots and designate the type of relationship (increasing/positive, decreasing/negative, or no relationship) observed in each one.
Determine what you can conclude from these relationships. You may include a copy of each chart in your report, but it is not required.
Section 3: Recommendations and implementation
Based on the findings, assess which expansion criteria seem to be more effective. Could any expansion criterion be changed or eliminated? If so, which one(s) and why?
Based on the findings, does it appear as if the loyalty card is positively correlated with sales growth? Would you recommend any changes to this marketing strategy?
Based on the findings, recommend market positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
Include how the local culture and communities are represented in your market position in your recommendations.
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 surveys/samples or census?)
Format your references according to APA guidelines.
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