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Unit outline_

PMGT6867: Quantitative Methods: Project Management

Semester 1, 2020 [Online] - Camperdown/Darlington, Sydney

Methods studied in this unit are used in a wide range of project management tasks and problems. The unit explains why and where particular methods are used and provides examples and opportunities to apply these methods in practice. This unit will also facilitate the understanding of the mechanics of these methods and their underlying theory.

Unit details and rules

Academic unit Civil Engineering
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Shahadat Uddin, shahadat.uddin@sydney.edu.au
Type Description Weight Due Length
Final exam Final exam
50% Formal exam period 1 hour
Outcomes assessed: LO1 LO4 LO3 LO2
Small test Class tests
30% Multiple weeks n/a
Outcomes assessed: LO1
Assignment group assignment Group assignment
Case study
20% Week 12 n/a
Outcomes assessed: LO2 LO3 LO4 LO5
group assignment = group assignment ?

Assessment summary

  • Class tests: The class test will comprise of short questions and exercises of different quantitative methods that are covered in previous weeks’ lectures. The mark for each class test is 10, and best 2 will be considered out of 3 class tests.
  • Group assignment: The group assignment is case study, which will be post via Blackboard in week 4, and is designed to develop student’s skills in actual applications requiring the use of different quantitative methods in interpreting data for decision-making.
  • Performance and presence in tutorials: Students need to attend each week’s tutorial and complete the exercises (both short questions and problem based on quantitative method taught in lectures) given by the tutorial. 
  • Final Examination: The final written examination (closed book) will be drawn from all aspects of the unit of study. 

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Multiple weeks Independent learning activities Independent study (100 hr) LO1 LO2 LO3 LO4 LO5
Week 01 Basic measures of number and QM for capital budgeting Online class (3 hr) LO1 LO4
Week 02 Network diagram and critical path method Online class (3 hr) LO4 LO5
Week 03 Probability and probability distribution Online class (3 hr) LO1 LO2 LO4
Week 04 Probability tree and decision table Online class (3 hr) LO1 LO2
Week 05 Deduction analysis: depreciation Online class (3 hr) LO4 LO5
Week 06 WBS and project estimations Online class (3 hr) LO3
Week 07 Correlation, regression, Pareto analysis, histogram and earned value analysis Online class (3 hr) LO3 LO4
Week 08 Fuzzy logic in project management Online class (3 hr) LO4 LO5
Week 09 Decision making approaches: payoff analysis and utility function Online class (3 hr) LO4 LO5
Week 10 The mathematics of project contracts Online class (3 hr) LO3 LO4 LO5
Week 11 Project forecasting Online class (3 hr) LO4 LO5
Week 12 Process capability and control chart Online class (3 hr) LO1 LO2 LO3
Week 13 Review of all previous course materials Online class (3 hr)  

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. explain the features of different quantitative methods used in a range of project management functions including budgeting, scheduling, quality management and forecasting
  • LO2. account for limitations and capabilities of each method in selecting and applying quantitative methods for different project management tasks
  • LO3. reliably interpret the numerical values generated by these methods, correctly apply them in project decisions, particularly where risk is involved
  • LO4. develop effective metrics for evaluating project success, based upon a sound quantitative analysis of the project's business value
  • LO5. explain and justify the results of quantitative analyses in clear simple terms to diverse project stakeholders.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

There are no specific attendence and class requirements for this unit

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.