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	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)
Obs	SqFt	Sales/Person	SalesGrowth%	LoyaltyCard%	Sales/SqFt	MedIncome	MedAge	BachDeg%
1	2354	6.81	-8.31	2.07	701.97	45177	34.4	31
2	2604	7.57	-4.01	2.54	209.93	51888	41.2	20
3	2453	6.89	-3.94	1.66	364.92	51379	40.3	24
4	2340	7.13	-3.39	2.06	443.04	66081	35.4	29
5	2500	7.04	-3.30	2.48	399.20	50999	31.5	18
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
11	2392	6.66	0.47	2.09	484.38	78497	36.2	39
12	2408	7.03	0.55	2.47	581.09	41245	32.2	23
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
15	1986	7.38	2.05	2.01	586.48	37950	34.3	24
16	2500	7.18	2.12	2.64	368.73	45206	32.4	17
17	2668	7.35	2.84	2.22	351.47	79312	32.1	37
18	2517	6.95	2.88	2.07	458.24	37345	31.4	22
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
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
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
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
27	2400	6.70	5.48	1.95	494.88	89016	36.4	34
28	2430	6.91	5.86	2.04	310.07	114353	40.9	34
29	2549	7.58	5.91	1.41	373.46	75366	35.0	30
30	2500	7.03	5.98	2.05	235.81	48163	26.4	16
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
33	2600	7.07	6.13	2.73	274.30	45723	31.3	18
34	2160	7.00	6.27	1.95	542.62	43800	29.6	36
35	2800	7.08	6.57	2.04	178.56	68711	32.9	18
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
38	2400	7.64	7.12	1.64	297.37	63657	37.3	29
39	2270	6.62	7.39	1.78	323.17	67099	39.8	25
40	2800	6.76	7.67	2.23	468.84	75151	33.9	28
41	2520	7.11	7.91	2.15	352.57	93876	35.0	40
42	2487	7.05	8.08	2.83	380.34	79701	35.0	39
43	2629	6.90	8.27	2.37	398.12	77115	35.9	30
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
46	2500	7.45	8.72	1.28	698.64	87863	38.5	29
47	2449	7.00	8.75	1.76	367.19	73752	40.5	19
48	2625	6.96	8.79	2.51	431.93	85366	32.1	29
49	3150	7.30	8.90	1.90	367.06	39180	34.8	18
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
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
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

Scenario:

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:

• Median age between 25 - 45 years old
• Household median income above the national average
• At least 15% college-educated adult population

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 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.

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.

• Section 1: Scope and descriptive statistics
• Section 2: Analysis
• Section 3: Recommendations and Implementation

Section 1 - Scope and descriptive statistics

• State the report's objective.
• Discuss the nature of the current database. What variables were analyzed?
• Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.

Section 2 - Analysis

• Using Excel, create scatter plots and display the regression equations for the following pairs of variables:
• "BachDeg%" versus "Sales/SqFt"
• "MedIncome" versus "Sales/SqFt"
• "MedAge" versus "Sales/SqFt"
• "LoyaltyCard(%)" versus "sales growth(%)"
• 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.

Section 3: Recommendations and implementation

• 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?
• 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?
• Based on your previous findings, recommend a marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
• 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?)