Great Deal! Get Instant \$10 FREE in Account on First Order + 10% Cashback on Every Order Order Now

# Resources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis Assignment Purpose This assignment is intended to help you learn how to apply statistical methods when...

Resources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis Assignment

Purpose

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.

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 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.

Report:

Write a 750-word statistical report that includes the following sections:

• 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 “SalesGrowth(%)”
• 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 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?)

Cite references to support your assignment.

Format your citations according to APA guidelines.

Answered Same Day Jul 01, 2021

## Solution

Sudharsan.J answered on Jul 04 2021
1
Pastas R Us, Inc. Database (n= 74 restaurants)
Scope and Objective
This research aims to gain useful insight into the relationship between the annual sales per Square feet and Median HH income, Median Age , Degree. And also between Loyality card percentage of net sales and Sales growth over previous year. This Chapter further discuss about the research method of sample about the restaurant taken from Pastas R Us, Inc. Database (n= 74 restaurants), the data analysis and Procedures.
Variable Used
The nature of the cu
ent database consists of all numerical continuous variable. It consists of 9 variables (plus 1 defines variable) and 74 observations. From the 9 variables, the following variables are used for analysis. (Sales Growth %, Loyaly Card %, Sales/Sq.ft, MedIncome, MedAge, BatchDeg% and Age-Group.
Descriptive Statistics
Table-1

SqFt
Sales/ Person
Sales Growth%
Loyalty Card%
Sales/SqFt
MedIncome
MedAge
BachDeg%
Mean
2580.47
7.04
7.41
2.03
420.31
62807.70
35.20
26.31
Standard E
o
43.58
0.03
0.77
0.06
15.95
2081.33
0.42
0.81
Median
2500.00
7.00
7.03
2.08
396.01
62757.00
35.00
26.50
Mode
2500.00
7.03
4.05
2.04
-
-
34.80
29.00
Standard Deviation
374.92
0.30
6.62
0.55
137.24
17904.27
3.65
7.00
Sample Variance
140564.28
0.09
43.89
0.31
18834.69
320562990.02
13.36
49.07
Kurtosis
3.76
0.85
1.15
1.45
2.88
-0.51
0.16
-0.94
Skewness
0.53
0.90
0.49
-0.76
1.24
0.30
-0.17
0.14
Range
2548.00
1.43
37.12
3.09
808.56
81424.00
18.80
26.00
Minimum
1251.00
6.54
-8.31
0.29
178.56
32929.00
24.70
14.00
Maximum
3799.00
7.97
28.81
3.38
987.12
114353.00
43.50
40.00
Sum
190955.00
521.26
548.64
149.96
31102.60
4647770.00
2604.90
1947.00
Count
74.00
74.00
74.00
74.00
74.00
74.00
74.00
74.00
Confidence Level(95.0%)
86.86
0.07
1.53
0.13
31.80
4148.08
0.85
1.62
Table-2
Age-Group
Frequency
Percentage
21-25
1
1.35%
26-30
8
10.81%
31-35
35
47.30%
36-40
26
35.14%
41-45
4
5.41%
Table-3
Age-Group
Sum of Sales/Person
Sum of SalesGrowth%
21-25
6.95
14.6
26-30
56.23
54.76
31-35
247.97
232.83
36-40
181.08
189.93
41-45
29.03
56.52
Grand Total
521.26
548.64
Table-4
Age-Group
Sum of MedIncome
21-25
42631
26-30
337473
31-35
2176163
36-40
1837000
41-45
254503
Grand Total
4647770
Analysis
Table-5 (Batch Deg Vs Sales Sq.ft)
SUMMARY OUTPUT

Regression Statistics

Multiple R
0.341947

R Square
0.116928

0.104663

Standard E
o
6.628047

Observations
74

ANOVA

df
SS
MS
F
Significance F

Regression
1
418.819
418.819
9.533562
0.002865

Residual
72
3163.032
43.93101

Total
73
3581.851

Coefficients
Standard E
o
t Stat
P-value
Lower 95%
Upper 95%
Intercept
18.97518
2.497617
7.597315
8.64E-11
13.99627
23.95409
Sales/SqFt
0.017453
0.005653
3.087647
0.002865
0.006185
0.028721
The fitted equation of the model is:
Batch Deg= 18.97518-0.017453*Sales/Sq.ft
Table-6 (MedIncome Vs Sales Sq.ft)
SUMMARY OUTPUT

Regression Statistics

Multiple R
0.022441

R...
SOLUTION.PDF