Units

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Sample subject outline - Semester 1 2013

Note: Subject outlines often change before the semester begins. Below is a sample outline.

Rationale

In an information society there is an increasing range and variety of workplaces in which data and statistical analyses are important in enabling good management and decision-making. This unit will introduce you to a range of statistical techniques in usage in a variety of disciplines and in business, industry and government workplaces.

Aims

This level 3 unit builds on your knowledge and skills of statistical techniques used across all disciplines, to provide you with sufficient working knowledge and understanding of more advanced statistical techniques to enable you to apply these in a range of real situations in diverse workplaces and disciplines.

Objectives

On completion of the unit you should be able to:

1. Explain the fundamental concepts underpinning a range of statistical techniques used in a variety of disciplines and workplaces.
2. Apply operational knowledge of workplace-oriented statistical techniques beyond the core basic methods.
3. Demonstrate skills in analytic and creative problem solving techniques in environments relevant to other disciplines and workplaces.

Content

The course will present a range of different statistical techniques, grouped into three sub-units.
These are:
1. Survival analysis
- Reliability analysis, for analysis of data which may compromise failure times, count or censored data.
- Modelling of survival times and counts.
2. Multivariate data analysis
- These include methods for data reduction such as principal component analysis and factor analysis, for unsupervised classification via clustering, and supervised classification such as discriminant analysis.
3. The design of experiments
- Experimental design concepts will be developed for guiding the collection of data to support specific analyses and experimental aims.
- Survey methodology will also be introduced.

In addressing these three sub-units, for each technique, we will present the core concepts required to understand, apply and interpret the results: defining the model and its underlying assumptions; an introduction to estimation and statistical inference (such as hypothesis testing and parameter estimation); and model assessment.

Approaches to Teaching and Learning

Your work will be context-based using a wide variety of examples from many different areas of application.

The emphasis will be on learning through experience, on learning collaboratively and as individuals, on written and oral communication, and on developing skills and attitudes to promote life-long learning.

A combination of discussion, working through small and larger real world problems, participating in data investigations and group work, and expressing solutions individually and in groups, will promote your creativity in problem-solving, critical assessment skills, and intellectual debate.

Discussion of misconceptions, poor practice and misuse of statistical tools will illustrate the need for professionalism and ethics in the practice of statistics.

Assessment

All assessment in this unit is skills-based and operational assessment. The focus is on problem-solving skills using operational knowledge and understanding of key concepts, techniques and procedures.

The assessment package is carefully designed to help you manage and optimise your learning throughout the semester, allowing for different individual situations and capabilities. The assessment package is designed to help you develop your understanding and skills throughout the semester, aiming for achievement of the synergies and synthesis of the unit by the end of semester.Timely summative and formative feedback is provided on all assessment, consisting of comments to assist students improve their understanding and problem-solving skills, and model solutions to all exercises and problems.

Assessment name: Problem Solving Task
Description: (Summative) - Continuous assessment. This will consist of problem solving exercises, which will develop your operational knowledge and skills in applying statistical techniques to real data. Exercises will be spaced regularly throughout the semester. You will be given a written schedule of due dates for these exercises. The criteria and standards will be given in writing with each exercise at least 2 weeks before the due date. The exercises will be marked with feedback to help with both understanding and communication skills. The exercises will reflect the three main sub-sections of the unit, and their weight will reflect the extent of data and data analysis needed.
Relates to objectives: All.
Weight: 40%
Internal or external: Internal
Group or individual: Individual
Due date: Throughout Semester

Assessment name: Examination (Theory)
Description: (Summative) - This three hour examination will consist of questions applying your work across the whole semester, with the emphasis on using techniques and interpreting output and results in context. You will be able to take your own summary sheet of material into the examination. Further details will be given as techniques are developed during the semester.
Relates to objectives: All.
Weight: 60%
Internal or external: Internal
Group or individual: Individual
Due date: Exam Period

Assessment name: Laboratory/Practical
Description: Laboratory/practical exercises are set each week, to explore and consolidate information presented during lectures. Timely summative and formative feedback is provided on these exercises, consisting of comments to assist students improve their understanding and problem-solving skills, and model solutions to all exercises and problems.
Relates to objectives: All
Internal or external: Internal
Group or individual: Group with Individual Component
Due date: Throughout Semester

Academic Honesty

QUT is committed to maintaining high academic standards to protect the value of its qualifications. To assist you in assuring the academic integrity of your assessment you are encouraged to make use of the support materials and services available to help you consider and check your assessment items. Important information about the university's approach to academic integrity of assessment is on your unit Blackboard site.

A breach of academic integrity is regarded as Student Misconduct and can lead to the imposition of penalties.

Resource materials

There are no required texts in this unit. Suggested reference books are:

1. Hastie, T., Tibshirani, R. and Friedman, J. (2008) The elements of statistical learning, 2nd edition, Springer-Verlag; available online at http://www-stat.stanford.edu/~tibs/ElemStatLearn/

2. Johnson, R. A.and Wichern, D. W. (2002). Applied Multivariate Statistical Analysis, Prentice and Hall.

3. Collett, D. (2003). Modelling Survival Data in Medical Research, Chapman and Hall.

4. Box, G.E.P., Hunter, J,S., and Hunter, W.G. (2005) Statistics for Experimenters: Design, Innovation & Discovery, John Wiley & Sons: New Jersey.

Risk assessment statement

There are no out of the ordinary risks associated with this unit. Emergency exits, evacuation procedures and assembly areas will be pointed out in the first few lectures. More information on Health and Safety can be obtained from the university's website http://www.hrd.qut.edu.au/healthsafety/healthsafe/index.jsp

Disclaimer - Offer of some units is subject to viability, and information in these Unit Outlines is subject to change prior to commencement of semester.

Last modified: 22-Oct-2012