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Assessment Details and Submission Guidelines

School

Business

Course Name

MasterofProfessionalAccounting

Unit Code

MA609

Unit Title

BusinessAnalyticsand Data Intelligence

Assessment Author

Dr Ken Mardaneh

Assessment Type

Assignment[individual]

Assessment Title

Assignment[individual]

Unit Learning Outcomes covered in this assessment

Demonstrate advanced and integrated understanding of business and data Intelligence for organisational decision-making. Analyse critically, reflect on and synthesise techniques of data visualisation and data mining.

Weight

20%

Total Marks

100Marks(thiswill bescaleddownto20%)

Word limit

Notapplicable

Release Date

Week3

Due Date

Week7

Submission Guidelines

All work must be submitted on Moodle by the due date along with a completed AssignmentCoverSheet. For Melbourne students: use Melbourne Campus Submission link. For Sydney students: use Sydney Campus Submissions link. Reference sources must be listed appropriately at the end in a reference list using APA referencing style.

Extension

If an extension of time to submit work is required, a Special Consideration Application must be submitted directly to the School’s Administration Officer, in Melbourne on Level 6 or in Sydney on Level 7. You must submit this application three working days prior to the due date of the assignment. Further information is available at: http://www.mit.edu.au/about–mit/institute–publications/policies–procedures–and–guidelines/specialconsiderationdeferment

Academic Misconduct

Academic Misconduct is a serious offence. Depending on the seriousness of the case, penalties can vary from a written warning or zero marks to exclusion from the course or rescinding the degree. Students should make themselves familiar with the full policy and procedure available at:http://www.mit.edu.au/about-mit/institute-publications/policies-procedures-and-guidelines/Plagiarism-Academic-Misconduct-Policy-Procedure.For further information, please refer to the Academic Integrity Section in your Unit Description.

Assessment Cover Sheet

Student ID Number/s:

Student Surname/s:

Given name/s:

Course:

School:

Unit code:

Unit title:

Due date:

Date submitted:

Campus:

Lecturer:

Tutor:

Student Declaration I/We declare that: the work contained in this assignment is my/our own work/group work, except where acknowledgement of sources is made; certify that this assessment has not been submitted previously for academic credit in this or any other course; I/we have read the MIT’s Plagiarism and Academic Misconduct Policy Procedure, and I/we understand the consequences of engaging in plagiarism; a copy of the original assignment is retained by me/us and that I/we may be required to submit the original assignment to the Lecturer and/or Unit Co-ordinator upon request;I/we have not plagiarised the work of others or participated in unauthorised collaboration when preparing this assignment.

MIT ID

Signature

Date

For Assessor Use Only (if not marked on Moodle)

Name:

Position

Date:

Signature:

Marks/Grades:

Assignment Description:

The assignment is designed to allow you to demonstrate effective business analytics skills using optimisation methods. You will need to use linear programming skills to conduct the analytics and obtain the solutions. This is individual assignment and each student will work independently.

Problem 1: Three objective functions for linear programming problems are 7A+10B, 6A+4B, and -4A+7B. Show the graph of each for objective function values equal to 420. (5 marks)

Problem 2: Consider below the linear programming problem: (5 marks)

Max 3A+2B

s.t.

1A+1B≤10

3A+1B≤24

1A+2B≤16

A,B≥0

Constraint

Constraint R.H. side

Allowable increase

Allowable decrease

1

10

1.20

2

2

24

6

6

3

16

Infinite

3

The value of the optimal solution is 27. Suppose that the right-hand side for consraint1 is increased from 10 to 11.

Use the graphical solution procedure to find the new optimal solution. (2 marks)

Use the solution to part (a) to determine the shadow price for constraint 1. (1 mark)

The sensitivity analysis for the linear program in this problem provides the following right-hand side range information:

What does the right-hand side range information for constraint 1 tell you about the shadow price for constraint 1? (1 mark)

The shadow price for constraint 2 is 0.5. Using this shadow price and the right-hand-side range information in part (c), what conclusion can you draw about the effect of changes to the right-hand side of constraint 2? (1 mark)

Problem 3: Maxwell Manufacturing makes two models of felt tip marking pens. Requirements for each lot of pens are given below. (5 marks)

Fliptop Model

Tiptop Model

Available

Plastic

3

4

36

Ink Assembly

5

4

40

Molding Time

5

2

30

The profit for either model is $1000 per lot.

What is the linear programming model for this problem (write objective function and constraints? (3 marks)

Show the solution graphically. (2 mark)

Let F= the number of lots of Fliptop pens to produceLet T= the number of lots of Tiptop pens to produce

Problem 4: For this problem: (5 marks)

Solve the following linear program graphically and, (2 marks)

Show the feasible region and, (2 mark)

Show the optimal point. (1 mark)

Max

5X + 7Y

s.t.

X ≤ 6

2X + 3Y ≤ 19

X + Y ≤ 8

X, Y ≥ 0

Note: Students need to submit the assignment as a word document.

MA609 Businessanalyticsand data Intelligence Assignment[Individual] Marking Guide (20 Marks)

Criteria

Possible Marks

Marks Allocated

Proper graphical representation of the models Comment:

10%

Accurate measurement of the graphs Comment:

10%

Identifying the feasible points Comment:

10%

Identifying the feasible region Comment:

20%

Identification of the range of optimality Comment:

20%

Indication of improvement in the value of optimal solutions Comment:

20%

Structure and Presentation of the assignment: Comment:

10%

Total

100%

Overall Comments:

Assessor Name:

Assessor Signature:

= _____/20__ Marks Date:

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