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PMGT5893: Statistical Methods in PM (2013 - Semester 1)

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Unit: PMGT5893: Statistical Methods in PM (6 CP)
Mode: Normal-Evening
On Offer: Yes
Level: Postgraduate
Faculty/School: Project Management
Unit Coordinator/s: Dr Harré, Michael
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Brief Handbook Description: Aims: Students should achieve an understanding of the applications of statistical methods in project environments.

Objectives: Students should be able to:

- Conduct hypothesis test and draw conclusions;

- Apply regression analysis to examine relationships between variables;

- Explain the relationships between variables;

- Describe the distributions of variables;

- Draw conclusions based on results observed in a sample;

- Discuss the application of statistical model for project selection;

- Apply statistical method for forecasting project time and cost at completion;

- Discuss the application of statistical model for cost estimating; and

- Apply R in analyzing and evaluating statisitcal information.

By the end of this unit of study, students should be able to:

- Discuss the applications of statistical methods;

- Evaluate a project situation based on statistical results; and

- Apply simple statistical methods to problem-solving in project management.
Assumed Knowledge: None.
Lecturer/s: Dr Harré, Michael
Timetable: PMGT5893 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 1.00 1 13
3 Independent Study 6.00 13

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Project Methods (Level 3)
1. Conduct hypothesis test and draw conclusions.
2. Apply regression analysis to examine relationships between variables.
3. Explain the relationships between variables.
4. Describe the distributions of variables.
5. Draw conclusions based on results observed in a sample.
6. Discuss the application of statistical model for project selection.
7. Apply statistical method for forecasting project time and cost at completion.
8. Discuss the application of statistical model for cost estimating.
9. Apply R in analyzing and evaluating statistical information
10. Discuss the applications of statistical methods in project management.
11. Evaluate a project situation based on statistical results.
12. Apply simple statistical methods to problem-solving in project management.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Quiz No 10.00 Multiple Weeks 1, 3, 4, 5,
2 Quiz No 10.00 Multiple Weeks 2, 6, 7, 11,
3 Assignment Yes 20.00 Multiple Weeks 1, 2, 4, 5, 6, 7, 8, 9, 11, 12,
4 Final Exam No 60.00 Exam Period 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
Assessment Description: Three Quizzes: The best two out of three results are counted towards 20% of the overall mark.

Project: Students develop a business case for a given project in groups and then as individuals critically evaluate the cases developed by others. This counts towards 20% of the overall mark.

Final Exam: 2 hours, covering all content from this unit.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: All university policies can be found at http://sydney.edu.au/policy

Policies and request forms for the Faculty of Engineering and IT can be found on the forms and policies page of the faculty website at http://sydney.edu.au/engineering/forms
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Introduction to the course, why stats and why this course
Week 2 Principles of Statistics
Week 3 Statisitics using the package R
Week 4 Variance and covariance
Week 5 Linear regression models
Week 6 Worked examples of linear regression
Week 7 A Worked Example of Regression Modelling
Week 8 ANOVA: Analysis of Covariance in R
Week 9 ARIMA Prediction of Time Series
Week 10 Statistics and Discounted Cash Flows
Week 11 Worked Examples from aother areas
Week 12 Bringing the concepts together
Week 13 Summary, questions, exam preparation
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Aeronautical Engineering / Project Management 2012
Aeronautical Engineering (Space) / Project Management 2012
Chemical & Biomolecular Engineering / Project Management 2012
Bachelor of Project Management (Hons) 2013, 2014
Graduate Certificate in Project Management 2012, 2013
Graduate Diploma in Project Management 2012, 2013
Master of Project Management 2010, 2011, 2012, 2013, 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Project Methods (Level 3) No 100%
Project Development (Level 3) No 0%
Project Delivery (Level 3) No 0%

These goals are selected from Project Management Learning Progression Table which defines overall goals for courses where this unit is primarily offered. See Project Management Learning Progression Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.