Solved by verified expert:Purpose of Assignment The purpose of this assignment is to develop students’ abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will develop the ability to use statistical analysis and verify whether or not a claim is valid before advertising it. Assignment Steps Resources: Microsoft Excel®, Spicy Wings Case Study, Spicy Wings Data Set Develop a 700-word statistical analysis. Use descriptive statistics to compute a measure of performance John can use to analyze his delivery performance. Find the following for your measures:MeanStandard deviationSample sizeFive-number summary on the total time Conduct a formal hypothesis testing to help John decide whether to offer the delivery guarantee or not. Estimate the probability of an order taking longer than 30 minutes. Make a recommendation in a short narrative including the following:Based on the sampled data, should John offer the guarantee?What percent of the Saturday deliveries would result in a customer receiving a free order?What recommendations might help John improve his Saturday delivery times?Format your assignment consistent with APA format. Click the Assignment Files tab to submit your assignment.
spicy_wings_case_study_week_5.doc
spicy_wings_dataset_week5_lta.xlsx
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Case Study – Spicy Wings Case Study
QNT/561 Version 9
University of Phoenix Material
Case Study – Spicy Wings Case Study
Following his graduation from the MBA program at the University of Phoenix, John Tyler wanted to live
and work in the little town of Hood. However, the community was small and there were not a lot of readily
available opportunities for college graduates. Fortunately, John had some experience working in the food
service industry gained in summers and throughout high school at his uncle’s restaurant in Franklin, a few
miles away from the town of Hood. When John decided to leverage his experience into a small delivery
and take-out restaurant located close to his home, he thought he had hit on a great idea. John would offer
a limited fare consisting of the buffalo wings his uncle had perfected at his restaurant. John called his
restaurant, Spicy Wings. Although success came slowly, the uniqueness of John’s offering coupled with
the growth of the community made Spicy Wings a success.
John’s business was pretty simple. John purchased wings locally. The wings were then seasoned and
prepared in John’s restaurant. Once an order was received, John cooked the wings, which were then
delivered or picked up by the customer. John’s establishment was small, and there was no place for
customers to dine in the restaurant. However, his wings proved so popular that over time, John hired
several employees, including three delivery drivers. Business was steady and predictable during the
week, with the biggest days being home-game football Saturdays.
A little over a year ago, the little town of Hood began to grow and expand. John noticed his business was
beginning to suffer when other fast-food delivery restaurants opened around the town. Some of these
restaurants were offering guarantees such as “30 minutes or it’s free.” John’s Spicy Wings now had to
compete with fish tacos, specialty pizzas, and gourmet burgers. Most of these new restaurants, however,
were dine-in establishments providing carry-out and delivery as a customer convenience. However, John
was certain he would need to offer a delivery guarantee to remain competitive with the newer
establishments.
John was certain a delivery guarantee of “30 minutes or it’s free” could easily be accomplished every day
except on football Saturdays. John thought if he could offer a 30-minute guarantee on his busiest day, he
would be able to hold onto and perhaps even recover market share from the competition. However,
before he was willing to commit to such a guarantee, John wanted to ensure that it was possible to meet
the 30-minute promise.
John knew it would be no problem for customers to pick up orders within 30 minutes of phoning them in.
However, he was less confident about delivering orders to customers in 30 minutes or less. Not only
would the wings need to be cooked and packaged, but the delivery time might be affected by the
availability of drivers. John decided he needed to analyze the opportunity further.
As a part of his analysis, John decided to take a random sample of deliveries over five different football
weekends. Cooking time and packaging time were not considered in his analysis because wings were not
cooked for individual orders. Rather, large numbers of wings were cooked at a single time and then
packaged in boxes of 12. John decided to focus his analysis on the time required to deliver cooked and
packaged wings. He collected information on the amount of time an order had to wait for a driver (the
pick-up time), as well as the amount of time required to transport the wings to the customer (the drive
time). The sampled information is in the Excel® file, Spicy Wings Data Set. John is not willing to offer the
guarantee on football Saturdays, unless he can be reasonably sure the total time to deliver a customer’s
order is less than 30 minutes, on average. John would also like to have an estimate of the actual time
required to deliver a customer’s order on football Saturdays. Finally, John would like to know how likely it
is the total time to make a delivery would take more than 30 minutes. Based on the sampled data, should
John offer the guarantee? What percent of the Saturday deliveries would result in a customer receiving a
free order? What recommendations might help John improve his Saturday delivery times?
Copyright © 2017 by University of Phoenix. All rights reserved.
1
Pick-up Time
4.94
0
4.98
5.03
4.15
4.67
5.01
3.88
2.8
2.71
2.79
4.73
5.2
4.18
5.57
2.73
4.4
0
3.41
4.16
3.6
5.45
0
3.96
4.54
0
4.21
3.22
0
5.55
6.35
5.14
6.11
3.95
4.54
2.23
4.99
4.83
5.03
3.56
5.15
5.69
3.59
3.39
2.77
Drive Time Total Time
26.96
31.9
21.73
21.73
19.74
24.72
20.08
25.11
19.04
23.19
16.17
20.84
14.93
19.94
23.92
27.8
17.15
19.95
20.97
23.68
25.83
28.62
15.41
20.14
15.53
20.73
17.02
21.2
23.2
28.77
18.19
20.92
20.94
25.34
17.46
17.46
16.33
19.74
22.54
26.7
23.52
27.12
3.3
8.75
22.87
22.87
18.31
22.27
24.82
29.36
13.22
13.22
19.64
23.85
14.11
17.33
23.69
23.69
15.04
20.59
21.59
27.94
10.81
15.95
20.46
26.57
15.56
19.51
22.54
27.08
25.29
27.52
22.81
27.8
23.45
28.28
21.01
26.04
21.94
25.5
24.63
29.78
24.13
29.82
15.52
19.11
28.15
31.54
22
24.77
Column A, Pick-up Time, is the amount of time (in
minutes) a packaged order had to wait to be picke
up by a delivery driver.
Column B, Drive Time, is the amount of time (in
minutes) required to deliver the packaged order t
the customer after it has been picked up by the
driver.
Column C, Total Time, is the total amount of time
Pick-upTime + Drive Time.
0
4.25
3.97
3.1
4.13
3.81
0
3.95
5.97
4.1
4.21
3.83
3.93
4.74
0
5.61
3.8
4.46
3.7
6.06
4.83
3.16
2.5
5.63
4.41
5.26
0
3.26
5.12
5.07
0
4.14
4.75
3.67
3.02
3.47
3.3
2.77
3.2
0
0
6.27
6.4
4.67
3.41
0
4.25
15.34
20.36
13.7
21.92
22.73
16.73
21.96
16.91
22.25
18.49
14.76
24.01
8.64
20.57
17.59
20.93
17
23.17
13.58
14
17.44
21.92
20.87
7.43
13.93
20.01
19.71
19.72
17.72
19.5
16.47
18.78
15.99
24.15
24.52
18.5
18.96
17.92
11.21
22.32
15.2
17.14
16.06
24.99
12.83
20.75
19.33
15.34
24.61
17.67
25.02
26.86
20.54
21.96
20.86
28.22
22.59
18.97
27.84
12.57
25.31
17.59
26.54
20.8
27.63
17.28
20.06
22.27
25.08
23.37
13.06
18.34
25.27
19.71
22.98
22.84
24.57
16.47
22.92
20.74
27.82
27.54
21.97
22.26
20.69
14.41
22.32
15.2
23.41
22.46
29.66
16.24
20.75
23.58
4.61
4.41
5.31
2.76
4.64
4.31
4.39
0
4.93
5.14
0
6.36
2.99
3.11
3.52
2.97
2.62
5.59
5.08
4.02
0
4.93
0
0
6.44
5.01
4.41
7.63
0
5.53
4.87
0
0
3.83
5.63
0
0
4.7
0
3.68
5.36
0
0
5.59
5.93
2.86
3.6
17.87
18.95
23.54
15.15
23.23
21.95
22.47
11.58
20.03
13.06
17.48
19.89
17.26
14.13
21.42
24.67
26.47
21.36
21.29
17.99
25.58
14.15
16.34
12.29
21.97
24.75
13.92
19.18
17.15
11.83
21.49
10.82
18.62
8.91
23.38
17.37
8.9
12.29
27.79
18.96
21.22
19.49
19.52
21.25
16.09
19.37
17.12
22.48
23.36
28.85
17.91
27.87
26.26
26.86
11.58
24.96
18.2
17.48
26.25
20.25
17.24
24.94
27.64
29.09
26.95
26.37
22.01
25.58
19.08
16.34
12.29
28.41
29.76
18.33
26.81
17.15
17.36
26.36
10.82
18.62
12.74
29.01
17.37
8.9
16.99
27.79
22.64
26.58
19.49
19.52
26.84
22.02
22.23
20.72
6.19
2.51
0
3.72
6.15
3.45
4.43
0
4.27
5.34
3.31
4.49
3.02
2.64
0
0
2.5
3.66
4.11
5.03
4.57
4.76
3.95
4.04
5.4
2.91
0
2.4
3.09
6.13
4.64
7.14
5.57
2.82
5.9
4.77
6.44
3.37
3.82
4.69
0
3.02
4.64
0
4.45
4.42
4.46
19.02
15.97
21.74
22.34
21.16
22.01
22.36
22.97
15
24.78
9.4
15.24
21.07
20.98
19.67
22.96
18.82
15.54
18.02
17.2
26.12
12.22
23.28
25.02
16.38
16.71
9.75
21.67
16.68
25.22
17.55
15.86
17.02
25.08
17.57
18.85
17.13
21.08
19.51
26.74
18.48
20.32
26.25
19.1
21.83
22.12
22.43
25.21
18.48
21.74
26.06
27.31
25.46
26.79
22.97
19.27
30.12
12.71
19.73
24.09
23.62
19.67
22.96
21.32
19.2
22.13
22.23
30.69
16.98
27.23
29.06
21.78
19.62
9.75
24.07
19.77
31.35
22.19
23
22.59
27.9
23.47
23.62
23.57
24.45
23.33
31.43
18.48
23.34
30.89
19.1
26.28
26.54
26.89
4.37
3.91
5.76
0
0
2.82
5.92
4.94
5.87
4.07
7.22
5.24
0
3.71
21.01
12.04
13.02
11.39
19.78
17.14
19.84
19.92
19.49
22.32
16.59
15.48
10.6
18.4
25.38
15.95
18.78
11.39
19.78
19.96
25.76
24.86
25.36
26.39
23.81
20.72
10.6
22.11
e, is the amount of time (in
rder had to wait to be picked
is the amount of time (in
eliver the packaged order to
as been picked up by the
is the total amount of time.
…
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