Description
mis171-assignment 2 -dashboard
Unformatted Attachment Preview
1250524d2e5bd6b026666309d058f6af
Database: Random Sample of 150 Superior Grocers Inc. business data, Year Ended June 30
Variable
Description
Sales $m: Total Sales revenue for each supermarket for the financial year. $ Million.
Wages $m: Total Wage for the financial year. $million
Wages %: Total Wage as a percentage of Total income.
No. Staff:
The number of effective full-time staff employed on a weekly basis.
Operating level
If number of staff is: (0-49 = Low, 50-99 = Medium, 100-150 High)
State:
Stores surveyed in different states
1 = California (CA)
2 = Texas (TX),
3 = Florida (FL),
4 = New York (NY).
Age (Yrs): The number of full years of operation of the store.
GrossProfit: Gross Profit for each supermarket for the financial year. $000.
Adv.$’000: Advertising and promotional expenses for the financial year, $’000
Competitors: The number of competing supermarkets in the consumer catchment area
HrsTrading: The total number of hours open for trading per week
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s Inc. business data, Year Ended June 30
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Database: Random Sample of 150 Superior Grocers Inc. business data, Year Ended June 30
Store No. Sales $m
1
10.7
2
12.7
3
17.2
4
16.4
5
5.8
6
16.7
7
11.3
8
13.1
9
15.3
10
7.4
11
8.5
12
17.5
13
6.3
14
7.3
15
13.9
16
8.0
17
17.7
18
14.4
19
6.2
20
10.4
21
9.3
22
15.0
23
10.0
24
12.2
25
8.7
26
4.4
27
15.1
28
6.1
29
7.8
30
14.5
31
9.4
32
11.3
33
6.2
34
14.3
35
8.6
36
5.6
37
8.7
38
10.2
39
12.7
40
4.1
41
7.2
Wages $m
4.0
4.4
4.8
4.3
3.7
4.4
4.1
4.2
4.4
3.8
3.9
4.8
3.5
5.0
4.5
3.8
5.5
4.3
3.6
4.3
4.1
4.7
3.7
4.0
4.0
3.3
5.1
3.2
3.6
5.4
4.3
4.2
3.5
5.6
3.7
3.5
4.0
4.0
4.1
3.6
3.6
Wages % No. Staff
17.3
53
17.6
73
15.5
97
13.4
59
25.7
44
13.5
55
17.2
54
15.5
52
14.8
58
21.6
48
20.4
58
15.0
80
21.4
36
35.0
95
16.6
60
20.8
55
18.6
142
15.3
60
22.2
44
20.1
75
20.3
58
16.6
123
15.9
44
15.7
49
21.1
53
24.3
33
19.3
112
17.6
28
18.5
44
21.9
144
22.2
73
18.5
54
21.5
37
23.1
140
18.1
46
22.9
37
20.8
51
18.2
53
15.4
47
30.7
41
20.4
46
State
CA
NY
NY
TX
TX
NY
CA
CA
NY
FL
NY
CA
FL
FL
NY
CA
TX
CA
TX
TX
TX
TX
TX
NY
CA
FL
NY
NY
CA
FL
FL
TX
TX
FL
FL
TX
FL
NY
TX
TX
TX
Age (Yrs)
9
7
6
6
14
5
6
5
7
15
9
6
22
2
8
15
8
7
11
12
2
7
7
6
2
13
11
5
5
11
13
6
2
2
3
11
14
4
8
1
12
GrossProfit $’000
98.10
36.00
134.40
164.10
241.70
228.80
93.10
96.90
120.60
33.40
241.30
51.70
187.60
189.30
226.40
85.70
155.70
217.70
126.90
39.00
42.80
255.30
106.80
118.00
108.20
124.50
188.10
164.90
76.70
35.30
130.50
122.90
144.90
124.30
158.40
124.30
43.60
120.60
172.50
28.70
110.90
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
14.0
12.2
13.5
12.6
13.0
10.3
6.2
6.6
8.8
9.1
6.9
7.7
5.0
5.4
9.5
7.6
6.8
15.3
13.6
9.2
13.8
5.8
9.6
21.7
10.6
11.6
12.0
9.8
10.0
10.6
6.3
7.7
6.6
7.2
13.7
8.6
10.9
12.2
7.6
12.2
14.1
5.7
6.3
8.5
5.2
4.2
5.1
4.8
5.3
4.2
3.6
3.7
3.7
4.0
3.8
4.2
3.4
3.3
4.3
3.7
3.5
4.6
4.1
3.9
4.7
3.5
4.1
5.3
4.9
4.4
4.2
4.0
4.3
4.3
5.0
3.7
3.5
3.5
4.8
3.8
3.9
4.7
3.7
4.2
4.2
3.3
3.6
3.8
21.0
17.0
21.1
20.3
23.2
19.4
23.1
22.9
18.0
19.9
22.6
25.1
24.4
21.8
21.8
20.5
19.9
15.8
14.7
19.0
17.9
22.8
20.3
14.3
24.8
19.3
17.4
18.7
20.7
19.7
39.4
20.0
20.8
18.5
18.8
19.1
16.1
20.2
19.7
16.5
14.4
19.8
22.3
19.6
123
52
148
110
135
49
44
49
44
49
46
55
37
34
80
48
41
88
51
44
60
43
51
125
90
75
56
48
49
50
98
46
40
32
85
44
44
82
43
73
59
36
42
42
NY
FL
FL
TX
TX
TX
FL
NY
CA
TX
CA
FL
TX
TX
FL
FL
FL
NY
FL
CA
TX
TX
NY
NY
TX
TX
NY
CA
TX
CA
FL
FL
TX
CA
NY
NY
CA
FL
CA
TX
CA
CA
TX
NY
17
4
1
21
1
3
1
13
2
8
1
20
3
11
3
13
9
4
5
5
12
2
1
7
18
4
11
2
1
6
1
18
9
8
3
4
6
17
10
4
8
4
15
2
126.90
142.80
37.30
120.50
223.70
280.50
68.60
156.80
142.40
226.80
314.10
100.30
157.90
114.80
176.50
92.40
191.30
108.80
189.20
135.30
173.00
80.10
160.50
128.70
140.40
154.90
88.10
100.80
141.10
174.50
81.50
156.40
178.10
37.20
45.40
90.50
44.10
129.30
181.40
56.00
36.10
74.90
125.20
215.00
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
5.9
6.7
8.9
5.6
13.0
5.5
5.8
7.2
11.1
7.2
16.4
12.6
7.0
10.7
11.5
10.7
11.4
9.3
6.5
7.5
6.4
13.0
8.9
7.0
7.9
7.9
8.7
7.1
6.1
19.2
10.9
7.6
5.7
10.0
9.6
5.4
18.6
8.0
14.4
9.6
16.5
6.9
7.3
7.9
3.6
3.6
3.9
3.5
4.3
3.6
3.5
3.6
3.8
3.6
5.3
4.7
3.7
4.2
3.9
4.1
4.5
4.2
3.6
3.6
3.4
5.0
3.7
3.8
3.7
3.6
3.9
3.4
3.5
5.0
3.9
3.6
3.5
3.5
5.3
3.6
5.0
3.6
4.6
4.0
4.9
3.5
3.5
3.5
23.4
21.6
19.9
22.6
16.3
24.9
23.1
20.4
15.3
20.1
19.0
20.1
21.8
18.7
15.2
18.6
20.3
21.8
22.4
19.2
20.1
21.5
17.4
22.9
19.9
18.6
19.7
18.2
21.8
14.8
16.7
18.9
23.2
13.9
30.4
25.9
15.0
18.7
17.2
19.6
16.8
20.2
18.7
17.5
39
46
55
44
74
49
35
49
53
41
123
88
49
53
51
65
80
75
42
48
42
82
46
51
47
48
58
32
35
130
58
42
44
46
135
49
98
57
70
58
133
46
37
39
CA
FL
NY
TX
CA
CA
CA
NY
CA
CA
TX
FL
TX
CA
NY
CA
NY
TX
TX
TX
CA
FL
TX
CA
FL
FL
NY
FL
TX
TX
TX
NY
TX
CA
FL
FL
TX
NY
CA
NY
NY
TX
CA
FL
2
20
7
3
5
23
1
2
4
11
11
4
2
16
5
9
14
19
3
10
12
5
3
12
1
3
2
6
3
5
5
9
17
6
0
3
6
4
8
8
5
9
13
6
289.50
83.70
114.80
135.20
109.70
182.90
169.70
167.30
134.10
45.20
168.10
88.10
76.50
174.90
67.20
112.50
210.50
67.70
39.30
35.40
112.10
219.60
128.70
113.30
89.50
165.30
85.90
34.10
155.20
34.40
116.80
151.70
50.00
178.10
110.00
39.20
40.00
180.80
90.60
54.40
98.00
146.90
149.60
223.20
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
4.8
7.3
7.9
6.0
12.1
8.5
9.9
7.6
7.7
6.9
11.0
4.8
15.2
14.9
14.1
6.1
12.3
6.3
11.8
8.2
9.8
3.3
3.9
3.8
3.8
4.1
3.9
4.7
3.5
3.6
3.8
4.6
3.4
4.7
4.7
5.1
3.7
5.0
3.4
4.6
3.7
3.9
22.9
23.1
20.7
25.7
16.6
20.1
24.8
17.8
18.8
22.7
22.1
24.6
16.8
17.1
20.4
24.1
22.6
20.4
20.7
18.5
17.6
51
55
55
39
59
49
101
37
37
44
75
37
88
72
112
44
124
51
59
48
53
TX
CA
NY
TX
NY
NY
TX
CA
CA
CA
FL
TX
NY
NY
TX
TX
FL
CA
NY
NY
CA
16
22
10
16
6
10
14
11
9
14
12
1
6
3
8
2
4
18
16
7
8
76.50
69.30
142.10
175.00
255.40
56.10
115.70
259.30
46.50
44.90
168.50
38.40
126.40
262.10
152.80
173.30
77.30
71.60
288.90
143.70
30.10
ata, Year Ended June 30
Adv.$’000 CompetitorsHrsTrading
159
3
102
201
5
126
243
2
90
275
1
77
100
0
64
226
0
69
112
2
92
202
2
87
203
3
104
142
5
127
85
2
92
300
2
88
111
1
64
136
0
65
216
1
78
124
4
113
357
1
77
175
0
65
54
1
82
104
0
74
132
6
160
189
0
72
84
6
137
122
3
104
89
3
98
70
2
93
299
4
116
53
1
80
19
4
109
237
6
146
185
0
64
201
2
93
57
0
64
189
1
83
57
1
70
105
1
88
69
4
112
199
3
104
139
0
64
65
6
142
87
3
102
271
184
241
191
152
134
109
116
120
63
132
140
92
100
127
138
48
254
197
169
168
99
138
336
202
129
136
134
187
159
110
98
61
77
154
106
105
163
90
170
218
47
59
34
2
2
6
3
1
1
4
1
2
0
0
3
1
3
1
3
3
1
1
2
1
4
2
2
2
2
3
3
2
1
4
1
0
5
5
3
6
0
3
5
5
4
2
1
96
91
137
103
78
76
115
89
90
64
65
103
78
112
76
100
110
84
80
93
83
112
90
90
90
88
108
106
90
83
121
80
74
127
125
104
160
70
102
124
129
119
104
77
31
113
106
89
201
103
109
57
166
73
270
144
74
200
145
79
157
163
65
113
90
237
122
117
39
21
109
104
56
284
153
80
97
113
187
101
272
103
176
127
220
71
88
101
0
3
3
2
5
1
1
1
2
4
0
4
3
1
2
3
0
2
5
7
3
2
1
4
2
2
3
7
1
5
4
2
3
2
3
5
5
0
0
4
2
2
2
1
66
101
100
92
160
79
76
79
93
122
64
121
92
78
90
104
77
88
142
160
100
70
78
125
99
92
100
147
82
129
132
90
103
93
101
124
129
64
68
116
91
82
90
77
88
111
94
114
188
35
190
85
37
72
197
58
173
197
163
106
241
8
91
108
90
4
6
2
2
4
3
5
2
3
4
1
5
2
0
1
3
4
4
2
3
5
128
160
88
89
116
103
139
93
103
114
77
129
91
67
76
107
116
131
94
106
127
Business Analytics – MIS171
Assignment 2
Trimester 3 2023
DUE DATE AND TIME:
Due by 11:59pm AEST Friday 15th December
PERCENTAGE OF FINAL GRADE:
20% of the final grade
Learning Outcome Details
ULO1:
ULO2:
ULO3:
ULO4:
Apply quantitative reasoning skills to analyse business problems.
Create data-driven/fact-based solutions to complex business scenarios.
Implement contemporary data analysis tools to analyse business performance.
Interpret findings and effectively communicate solutions to business scenarios.
Assessment Feedback:
Students who submit their work by the due date will receive their marks and feedback on Moodle within 15 business
days. Your assignment feedback will be returned in a rubric via Moodle with an overall mark together with comments.
To understand the areas where improvement is required, students are expected to refer, and compare their answers
to the suggested solutions and discuss further improvements with the teachers.
General Description / Requirements
The assignment requires that you analyse a data set, interpret, draw conclusions from your analysis, and then convey
your conclusions in a written report. The assignment must be completed individually. The assignment must be
submitted by the due date electronically in Moodle using the assignment submission link (Turnitin).
When submitting electronically, you must check that you have submitted the work correctly by following the
instructions provided in Moodle. Please note that we will NOT accept any hard copies or assignments submitted via
email. The assignment uses the Microsoft Excel file ‘Assignment 2 T3 2023’ which can be downloaded from Moodle.
The assignment must be completed individually.
The assignment focuses on materials presented up to and including Week 6.
The assignment must include two files:
1. An Excel file
2. A Word file
Scenario
Superior Grocers Inc.
Background
Superior Grocers Inc. is a major player in the U.S. retail market, with a strong presence in grocery and general
merchandise. The company originated from a small chain of family-owned grocery stores and has now expanded to
include numerous supermarkets across the United States. Each major city in the U.S. houses a regional office, with the
corporate headquarters located in New York City. The Data Analytics and Research department, based in the New York
headquarters, plays a crucial role in providing insights and statistical analysis for:
i. Overall sales performance of the company.
ii. Store operational efficiency and business hours.
iii. Employee performance and their impact on sales.
iv. Market competition and positioning.
As a senior analyst in the department, you, Jordan Smith, have received an email from the Chief Data Officer (CDO),
Taylor Johnson, outlining specific analytical tasks.
Your report must include two files:
1. An Excel file, which will include:
• your analysis (which answers Taylor’s specific questions),
• the interactive dashboard to be used by the CEO.
Additional analysis will not be marked. However, you can perform additional analysis if it will improve your report or
dashboard.
2. A Word file, which will include your report to Taylor
Data file
Taylor has provided you with an Excel data file of a random sample of 150 stores operated in the financial year
2022/23. The file includes a Data Description tab which describes the different data fields in the sample (and some
data fields which you will need to create from the numeric data provided):
Variable
Sales $m:
Wages $m:
Wages %:
No. Staff:
Operating
level
State:
Age (Yrs):
GrossProfit:
Adv.$’000:
Competitors:
HrsTrading:
Description
Total Sales revenue for each supermarket for the financial year. $ Million.
Total Wage for the financial year. $million
Total Wage as a percentage of Total income.
The number of effective full-time staff employed on a weekly basis.
If number of staff is: (0-49 = Low, 50-99 = Medium, 100-150 High)
Stores surveyed in different states
1 = California (CA)
2 = Texas (TX),
3 = Florida (FL),
4 = New York (NY).
The number of full years of operation of the store.
Gross Profit for each supermarket for the financial year. $000.
Advertising and promotional expenses for the financial year, $’000
The number of competing supermarkets in the consumer catchment area
The total number of hours open for trading per week
Email from the Chief Data Officer
To: Jordan Smith
From: Chief Data Officer, Taylor Johnson
Subject: Analysis of Recent Market Survey Data
Dear Jordan,
In our recent executive meeting, the board has directed us to conduct an in-depth analysis of a market survey
conducted six months ago. We need your expertise in this analysis and require a comprehensive report. Please
address the following points:
1. Analysis of Store Performance by Region:
Objective: To analyze the average revenue by store activity level (low, medium, high).
Approach:
• Create a variable called “Operating level” by converting the numerical variable “No. staff” to a categorical
variable based on the information provided in the Data Description sheet and the above table,
• Create suitable tables of summary statistics and at least one graph
• Produce the relevant tabulated summary statistics and graph(s).
• Calculate a 95% confidence interval for average Revenue for each operating level.
• in the “Conclusion” section write a (one sentence) conclusion for each Sales category (e.g., “I am 95%
confident…”).
2. Comparative Analysis of Store Distribution by State:
Objective: Determine if there is a significant difference in the distribution of stores across four key states: California
(CA), Texas (TX), Florida (FL), and New York (NY).
Approach:
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Calculate the proportion of the number of stores surveyed in California (CA), Texas (TX), Florida (FL), and New
York (NY).
Produce the relevant tabulated summary statistics and graph(s).
Calculate, compare and contrast, 95% confidence interval estimates for the proportion of stores in California
(CA), Texas (TX), Florida (FL), and New York (NY).Make sure that you interpret your findings.
In the Conclusion section, write a (one sentence) conclusion for each State (e.g., “I am 95% confident…”).
In the Conclusion section, in one sentence, answer the question “Is there any state that is represented
proportionally more (or less) than the others?
3. Profit Distribution Analysis:
Objective: Analyze the probability distribution of profits across different states.
a) What is the probability that Profit exceeds $180,000 in CA, TX, FL, and NY?
b) What is the probability that Profit would be less than $80,000 in CA, TX, FL, and NY?
c) What is the minimum value of Profit that only the top 20% of the stores in each of the 4 state (CA, TX, FL,
and NY) will achieve annually?
Approach:
Q.3(a):
• For each states (CA, TX, FL, and NY) calculate the probability of Profit exceeding $180,000
• Produce descriptive summary statistics and find relevant information to apply for the probability
calculations.
• In the Conclusion section write a (one sentence) conclusion for each state’s profit (e.g. “The
probability that Total profit…”).
Q3(b)
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Q3(c)
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For each states (CA, TX, FL, and NY) calculate the probability of Profit less than $80,000
In the Conclusion section write a (one sentence) conclusion for each state’s profit (e.g. “The
probability that Total profit…”).
For each state identify the relevant z-score and use it to calculate the respective profits,
In the Conclusion section write a (one sentence) conclusion for each state (e.g. “The profit for……”).
4. Hypothesis Testing on Average Profit and Sales Proportion:
a. It has been suggested at our most recent meeting that the average Profit of the 4 states CA, TX, FL, and NY are
now more than $120,000. Does this data confirm this hypothesis? (Use 5% level of significance)
Approach:
Q.4(a)
• Use a 5% Level of Significance (α = 5%)
• Conduct appropriate hypothesis test for Profit of each state (CA, TX, FL, and NY).
• In the Conclusion section write a (one sentence) conclusion for profit (e.g., “At a 5% level of
Significance…”).
4.b. Further, is there sufficient evidence to conclude that the proportion of sales in any state is below 35% of all
sales?
Hint: To answer this question, you will need to conduct appropriate hypothesis testing for each state
separately (using 5% significance level).
Finally, include an interactive Dashboard to explore the performance of Wages, Number of staff and Gross profit.
Your analysis and findings are critical for our upcoming strategic decisions. We look forward to your insights and the
dashboard.
Best regards,
Taylor Johnson
Assignment instructions
The assignment consists of three parts:
Part 1: Data Analysis
When conducting the analysis, you will apply techniques from descriptive analytics, visualisations, probabilities, and
confidence interval calculation. Hence, you will use various tables, graphs, and summary measures. When exploring
data, we often produce more results than we eventually use in the final report, but by investigating the data from
different angles, we can develop a much better ‘feel’ for the data: a deeper understanding of the data.
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Always ensure that you consider relevant modelling assumptions such as considerations of the level of
measurement of the variable, the method of sampling, the shape of the population distribution, and the sample
size.
The analysis section you submit should be on Q1 to Q4 sheets of the Excel file.
Where possible, it is always useful to produce both numerical and graphical statistical summaries as sometimes,
something is revealed in one that is not obvious in the other.
Your analysis should be clearly labelled and grouped around each question.
Poorly presented, unorganised analysis, or excessive output will be penalised.
Part 2: Report
You are required to reply by email, detailing all essential information and relevant conclusions from your data analysis.
You are allowed no more than 2 pages to cover your written conclusions. Please use the font size 11 (Arial), 1.5 line
spacing and leave a margin of 2.54 cm.
Please consider the following dot points very carefully.
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Keep the English simple and the explanations succinct. Avoid the use of technical statistical jargon.
Your reader will not necessarily understand complicated statistical terms, thus your task is to convert your analysis
into plain, simple, easy to understand language.
The email is to be written as a stand-alone document. Thus, you should not have any references in the email to
your analysis, nor should you include any charts and tables in your email.
Use an email format for your reply. That means the email heading (e.g. To: From: Subject 🙂 should be included,
the recipient should be addressed at the beginning and the signature or name of the sender should be included at
the end.
When composing your reply, make sure that you actually answer the questions asked.
Do not copy the questions in the email.
Sequentially number your answers in both your email and your analysis (1, 2 …) to match the email.
Include a simple introduction at the start of the email and a summary/conclusion at the end.
Marks will be deducted for the use of technical terms, irrelevant material, poor presentation / organisation /
formatting and emails that are over two pages long or copy questions in the email.
When you have completed the email, it is a useful exercise to leave it for a day, return to it and re-read it as if you
knew nothing about the analysis.
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Does it flow easily?
Does it make sense?
Can someone without prior knowledge follow your written conclusions?
Often on re-reading, you become aware that you may have made some unclear points, and find that you can rephrase them much more clearly.
Part 3: Interactive Dashboard
The minimum requirement is a neat, functional, interactive dashboard. It is expected that the dashboard includes up
to 5 interactive components.
The Microsoft Excel file should contain a separate sheet for the interactive Dashboard.
The following questions will help guide you in designing an interactive dashboard.
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What are the most appropriate visualisations for the dashboard?
What about the choice of colour?
How can I make the dashboard interactive?
Submission Instructions
Your submission will comprise of two files:
1. Your report in Microsoft Word format.
2. A Microsoft Excel workbook file (Containing: Your Analysis including all the graphs, charts etc.).
3. Submission should have the following format: MIS171_T3_StudentID.doc (or .docx) and
MIS171_T3_StudentID.xls (or .xlsx).
4. This assessment is to be submitted ONLINE ONLY into the Assessment 2 Turnitin link available on the MIS171
Moodle site.
5. All work you submit is checked electronically or by other means to detect potential collusion and/or plagiarism.
6. When you are required to submit an assignment through Moodle (Turnitin link), you will receive an instant
notification on the screen confirming that it has been submitted.
Notes
Penalties for late submission:
The following marking penalties will apply if you submit an assessment task after the due date without an approved
extension:
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5% will be deducted from available marks for each day up to five days, and work that is submitted more than five
days after the due date will not be marked and you will receive 0% for the task.
‘Day’ means working day for paper submissions and calendar day for electronic submissions.
The Unit Coordinator may refuse to accept a late submission where it is unreasonable or impracticable to assess
the task after the due date.
For more information about academic misconduct, special consideration, extensions, and assessment feedback,
please refer to the unit outline or Deakin College student portal.
Requests for Extensions:
Students who are unable to submit an assignment by the due date, due to exceptional circumstances, may contact the
Unit Coordinator ([email protected] ) to discuss options. Please submit evidence of the progress on your analysis
and the extension request via email.
Before contacting the Unit Coordinator, you must obtain appropriate documentation to support your request. You
must be able to demonstrate exceptional circumstances.
All requests must be made prior to the due date.
Good luck!
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