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MGMT90141 Business Analysis & Decision Making
创建日期：2024-06-17 16:52:22
标签： MGMT90141
Business Analysis & Decision Making

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MGMT90141

Business Analysis & Decision Making

Subject Outline
Introduction
Welcome to MGMT90141 Business Analysis and Decision Making.
This subject will focus on developing students’ understanding of a wide variety of strategic
and operational business problems and decisions being faced by managers and decision
makers in the fields of financial management, human resource management, marketing
management, operations management, and international business management. Students
will be shown how to use a range of quantitative approaches to analyze business problems
and, based on these analyses, make effective decisions. The subject will take descriptive
analytic, predictive analytic, and prescriptive analytic approaches. Students will be expected
to be able to calculate and manipulate data as well as interpret the results in order to derive
and evaluate alternative solutions to typical business problems.
The teaching team in this subject look forward to working with you to ensure that your
experience in this subject is an interesting, challenging, and rewarding one.
Subject Overview and Aims
The overall aim of this subject is to demonstrate how a series of business problems and
decisions is analyzed and resolved through the application of quantitative approaches.

Learning Outcomes
Learning Outcomes and Generic Skills
To view the subject objectives and the generic skills you will develop through successful
completion of this subject, please see the University Handbook:
Awareness Issues
At a broader level, studying this subject will increase your awareness of issues, such as the
role of and limits to quantitative approaches, under conditions of varying levels of uncertainty,
in the decision making process.

Eligibility and Requirements

Academic Staff Contact Details
Please see the subject LMS site for full contact details of the teaching staff in this subject.
Subject Coordinator Contact Details
• Prof. William Ho
Email: [email protected]
Consultation Hours: Please email me for consultation booking.

Email Protocol
Please note that we are only able to respond to student emails coming from a University email
address. Please do not use personal email addresses such as gmail or even business email
addresses. Emails from non-University email addresses may be filtered by the University’s
spam filter, which means that we may not receive your email. All correspondence relating to
this subject will only be sent to your University email address. Note that you must first activate
your University email address before you can send or receive emails at that address. 
While academic staff endeavor to address queries received via email, it is more appropriate to
resolve substantive questions during lectures and during normal consultation hours. With this
in mind, we encourage students to attend all lectures and to familiarise themselves with the
consultation hours offered by the lecturers in this subject.

Lecture Participation Requirements
Students are required to attend all the lectures during the semester. Prior to attending the
lectures, students are expected to read the equivalent chapters of the recommended
textbooks and the lecture slides and attempt the questions in the lecture slides in order to be
able to satisfactorily participate and contribute to the discussions during the lectures.
Lecture Schedule
This section provides a timetable of lectures for the entire semester. Note that the non-
teaching period is from Friday 29 March to Sunday 7 April 2024.
Week Date
Commencing
Topic Reading
1 26 February Introduction to Business Analytics
and Linear Programming (LP)
Anderson et al., 2019:
Chapters 1 to 3
2 4 March LP Applications Anderson et al., 2019:
Chapter 4
5
3 11 March LP Applications and Extensions Anderson et al., 2019:
Chapter 6
4 18 March Integer Programming (IP)
Applications
Anderson et al., 2019:
Chapter 7
5 25 March Decision Analysis with Perfect
Information (Assignment 1 due)
Anderson et al., 2019:
Chapter 13
6 8 April Decision Analysis with Sample
Information
Anderson et al., 2019:
Chapter 13
7 15 April Descriptive Statistics and
Probability Basics
Anderson et al., 2020:
Chapters 3 and 4
8 22 April Probability Distributions Anderson et al., 2020:
Chapters 5 and 6
9 29 April Linear Regression Anderson et al., 2020:
Chapter 14
10 6 May Multiple Regression Anderson et al., 2020:
Chapter 15
11 13 May Revision and Mock Examination
(Assignment 2 due)

12 20 May Group oral presentations
Lecture Slides / Materials
Lecture slides will be placed on the LMS prior to each lecture. The lecture slides are located
under the heading “Modules”.
Recorded Lectures
Audio and video recordings of lectures delivered in this subject will be made available for
review. These recordings allow you to revise lectures during the semester, or to review them
in preparation for the end of semester exam.
You can access recorded lectures by clicking on the Lecture Recordings (or similar) menu item
on the LMS page for this subject.
Please note that for live classes, recordings are not a substitute for attendance; rather they
are designed for revision. On rare occasions the recordings can fail to take place due to
technical reasons. In such cases, a substitute recording will be made available.
6
Private Tutoring Services
The Faculty has become increasingly concerned about the existence of a number of private
tutoring services operating in Melbourne that heavily target University of Melbourne students
enrolled in FBE subjects.
Students are urged to show caution and exercise their judgement if they are considering using
any of these services, and to please take note of the following:
Any claim by any of these businesses that they have a “special” or “collaborative” or
“partnership” style relationship with the University or Faculty is false and misleading.
Any claim by a private tutoring service that they are in possession of, or can supply you with,
forthcoming University exam or assignment questions or “insider” or “exclusive” information is
also false and misleading.
The University has no relationship whatsoever with any of these services and takes these
claims very seriously as they threaten to damage the University’s reputation and undermine
its independence.
It is also not appropriate for students to provide course materials (including University
curricula, reading materials, exam and assignment questions and answers) to operators of
these businesses for the purposes of allowing them to conduct commercial tutoring activities.
Doing so may amount to misconduct and will be taken seriously. Those materials contain
intellectual property owned or controlled by the University.
We encourage you to bring to the attention of Faculty staff any behaviour or activity that is not
aligned with University expectations or policy as outlined above.
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