Units

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Sample subject outline - Semester 2 2013

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

Rationale

Applied statistics provides methods for investigating relationships between variables that arise in data from a variety of areas including science, technology and commerce. The planning of the collection of the data, using ideas of experimental design, and the analysis of the resulting data, using methods based on statistical inference, are fundamental aspects of the statistical process. In addition, communication of results with clear reporting of the conclusions of the analysis is very important. These activities are an important part of decision making processes whatever the context of the application.

Aims

This unit is concerned with building on the experimental design and statistical analysis methods presented in undergraduate units in order to advance your knowledge of modern statistical methods. Additionally, the use of statistical software to carry out analyses and the reporting of conclusions are emphasised.

Objectives

On successful completion of this unit you should have:

1. Acquired expertise in the practice of statistical analysis through using statistical models in the analysis of various data sets and examples.
2. Developed skills in using statistical software packages such as SAS.
3. Demonstrated the communication of statistical conclusions in clear and concise written English.
4. Carried out an independent investigation of a non-core topic.

Content

The core content is given below in items 1-4 while additional topics are given in items 5-6:

1. Development of basic statistical software (e.g. SAS) programming skills.
2. Modelling continuous responses using Normal regression.
3. Modelling binary data using Binomial regression.
4. Modelling count data using Poisson regression.
5. Modelling categorical data using Multinomial regression.
6. Modelling categorical data using log-linear models.

Approaches to Teaching and Learning

There will be four contact hours per week. This will include 3 hours of lectures and 1 hour of computer laboratory practical.

You will have access during the semester to course unit material in a variety of forms including lecture notes, selections from texts, worked programming examples, and solutions to exercises. These will be available through QUT Blackboard.

Lectures will introduce various new topics and allow time for discussion and assistance. The practical will be used as time for you to develop solutions to the various exercises, for you to use statistical software (e.g. SAS) and discuss various aspects of the analyses with the demonstrator.

Your work will be context and case based using a wide variety of examples from many different areas of application. The emphasis will be on enabling your learning through experience, both in groups and as individuals, on providing opportunities to enhance your written and oral communication, and on further developing skills and attitudes to promote your lifelong learning.

This unit is being taught concurrently with an undergraduate offering of the same subject. University policy permits that postgraduate and undergraduate students attend the same lectures. Separate practical/discussion groups will be provided for postgraduate student where numbers allow. As a postgraduate student you will be required to complete separate or additional assessment. For this unit this means that you will write a report on additional advanced topic(s).

Assessment

In general, assessment is designed to give you progressive feedback during semester on your acquisition of capabilities. The range of assessment types reflects the relative importance of statistical problem solving, knowledge of relevant basic content, and skills in applying data analytical methods.Assessment carried out during the teaching period will be marked, with written comments, and returned promptly after submission deadlines as required by University policy. Examination scripts can be perused after the release of official results in the unit. The lecturer and demonstrators will be reasonably available for consultation in case of queries over marking of assessment items.

Assessment name: Problem Solving Task
Description: (Formative and Summative). This will consist of regular assignments based on the core content of the unit and at least one advanced topic. By the end of week 1 you will be given an approximate schedule of due dates for the assignments, but the class may request changes to this schedule. The assignments will help you with both understanding and communication skills. Your marked assignments, with feedback, will be returned to you within two weeks of submission of each assignment. Each assignment may be assigned as a group project: this will be confirmed during the first week of classes.
Relates to objectives: Relates to learning outcomes: All
Weight: 60%
Internal or external: Internal
Group or individual: Individual
Due date: Throughout Semester

Assessment name: Examination (Theory)
Description: (Summative). This will consist of an open book School-based exam based on the content covered over the entire semester. The exam will be held at approximately the end of semester, possibly in the examination period: this will be confirmed during the fist week of classes.
Relates to objectives: Relates to learning outcomes: 1-3
Weight: 40%
Internal or external: Internal
Group or individual: Individual
Due date: End of Semester

Assessment name: Laboratory/Practical
Description: (Formative). Each week you will be given the opportunity to discuss and solve practical exercises. Solutions will be provided so that you may compare your attempts and clarify any errors or misunderstandings.
Relates to objectives: Relates to learning outcomes: 1-3
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

Text:

Detailed lecture notes and other course unit material will be made available on QUT Blackboard.

References:

1. Dobson AJ & Barnett AG (2008), An Introduction to Generalized Linear Models, 3rd edition, Chapman & Hall, Boca Raton.

2. McCullagh P & Nelder JA (1989), Generalized Linear Models, Chapman & Hall, London.

3. Myers RH, Montgomery DC & Vining GG (2002), Generalized Linear Models: With Applications in Engineering and the Sciences, Wiley, New York.

4. Yandell BS (1997), Practical Data Analysis for Designed Experiments,Chapman & Hall, London.

5. Der G & Everitt BS (2002), A Handbook of Statistical Analyses using SAS, 2nd edition, Chapman & Hall, Boca Raton.

6. Thompson MH, Pettitt A, Mackisack M, Stephens F & Fanning A (2010), An Introduction to SAS for Statistical Data Analysis, QUT Manual.

7. Chatfield C (1995), Problem Solving: A Statistician's Guide, 2nd edition, Chapman & Hall, London.

Risk assessment statement

There are no out of the ordinary risks associated with this unit. You should be conscious of workplace health and safety at all times. Fire exits in classrooms will be indicated in the first class (absentees should obtain advice when they next attend). In the event of a fire alarm sounding, or on a lecturer's instruction, you should leave the room and assemble in the designated area which will be indicated to you. You should not attempt to adjust or repair computer or other electrical equipment, and should report suspected faults to a Computer Systems Officer. Further information on health and safety at QUT can be found at http://www.hrd.qut.edu.au/healthsafety/

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: 12-Oct-2012