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

Variation, data and processes involving at least some elements of randomness occur in various forms in all areas of engineering. This unit provides the foundation skills and knowledge in statistics that are needed across all modern workplaces and disciplines that make use of quantitative information, and on which developments and ongoing learning specific to different engineering areas are built. The unit includes: the planning, execution, analysis and reporting of data investigations; use of a statistical package; modelling data; relationships between variables; estimation; confidence intervals; tolerance limits; hypothesis testing; fitting and investigating relationships; multiple regression; design and analysis of experiments; probability and conditional probability basics; risk; random variables; special distributions; linear combinations of correlated variables; reliability.

Statistical modelling and methods provide a logical and consistent basis for handling and analysing data and systems involving variation, and are therefore relevant to all scientific and engineering disciplines. Thus, a basic grounding in statistical principles, concepts, techniques and models, including probability and distribution models, which are applicable to modern engineering, and which may be built on in later engineering studies is imperative for an engineering student. The data topics emphasize planning, carrying out and reporting on data investigations in real and familiar contexts, and the introduction to probability and distributions is oriented to needs across all engineering.

Aims

This unit will provide you with the foundation knowledge and skills to carry out a statistical data investigation including defining the problem, planning the investigation, collecting and analysing data, and reporting conclusions in context. It will also provide you with foundation knowledge and concepts of probability, random variables and distributions for further learning in engineering.

Objectives

On completion of this unit, you should be able to:

1. Understand the foundation concepts and application of introductory probability and distributions in building and analysing models of real processes.

2. Understand the importance in all aspects of a modern and technological society, of responsible and accountable collection, handling and description of data and variation, and of modelling and interpreting variation.

3. Demonstrate skills in the planning, implementation, analysis and reporting of data investigations.

4. Demonstrate general problem solving skills, including the ability to define problems and select appropriate methods of analysis, to communicate technical results clearly, and to work cooperatively in group situations.

Content

Probability and risk: conditional probability and Bayes theorem; random variables; discrete and continuous distributions and their parameters; special distributions: binomial, Poisson, exponential, uniform. Correlation and linear combinations of random variables; normal case.

Planning data investigations; collecting and handling data; choosing, producing and interpreting appropriate graphs and data summaries. Categorical variables and data: testing independence of two categorical variables; interval estimation of proportions. Continuous data and relevant parameters; standard errors and interval and prediction estimation. Experimental design, factors, interaction, ANOVA, multiple comparisons, residuals and model diagnostics. Modelling relationships between continuous variables; linear models; correlation; regression diagnostics; normal probability plots; calibration; multiple and polynomial regression; indicator variables and common mistakes in regression; general linear model.

Introduction to analysis of failure time data; exponential and Weibull; 'bathtub' curve.

Approaches to Teaching and Learning

The approaches of this unit emphasize example-based teaching and learning with constant references to familiar contexts as well as relevant engineering contexts and applications; interactive practicals with allowance for both individual and group work; separate workshops enabling students to practise the concepts and procedures introduced in lectures; logical and consistent development of unit to satisfy quantitatively and technically inclined students, but with emphasis on learning by doing; emphasis on assignments as part of the learning process, with timely feedback. The group project on a topic of your choice enables you to experience the whole process of tackling real problems, from identifying what is of interest through data collection, exploration and analysis, to writing a final report. It includes 'learn-as-you-go' aspects, but because you choose your own context of interest, it helps you identify with the methods you are meeting, and to realise the importance of methodology. Practical exercises will help to develop your skills in analysing data using a statistical computer package, and in applying methods to problems. These practical exercises are essential to help you develop understanding of the statistical analysis and modelling of data, to learn technical skills, and to develop problem-solving capabilities with problems that involve data and random variables. As they guide you through the techniques and computer-based procedures in analysing data, they are also of particular assistance for your projects. The workshop classes are structured to enhance your engagement with the concepts and procedures presented in lectures, as you learn to apply them to relevant example problems. Your demonstrators will provide guidance during this process by providing individual assistance, by demonstrating the solution process to you on selected examples and by facilitating collaborative work in problem-solving.

Assessment

All formative and summative assessment is designed to assist students with their learning and development of skills and knowledge throughout the semester. Ongoing participation in all formative and summative assessment is highly recommended to optimise learning in this unit. Further assessment details will be provided on Blackboard.Full solutions will be provided in a timely manner for all formative and summative assessment in problem-solving throughout the semester. Feedback on individual work will also be provided during workshop and practical classes. Ongoing guidance will be provided with group projects; in particular, feedback will be provided to each group on its proposed topic and plan; groups are also welcome to discuss their data and relevant methods for analysing it with teaching staff at all stages.

Assessment name: Problem Solving Task
Description: (Formative/summative). These consist of quizzes, practical exercises and problems in class strategically timed to optimise your learning. They cover the core operational knowledge and skills of the unit and provide you with an excellent way of learning through applying techniques to real data and real problems within context.
Relates to objectives: All.
Weight: 35%
Internal or external: Internal
Group or individual: Individual
Due date: Throughout Semester

Assessment name: Project (applied)
Description: (Formative/summative). Whole semester group project on context of your choice; identification of questions of interest; planning, collection, handling of data; exploration, presentation, analysis of data; reporting in context. Criteria and guidance will be available in a briefing/handout on Blackboard in week 2. You are encouraged to form your own groups of 4 people, although size of the group may be varied by 1 person with advance approval. Assistance will be provided in forming groups if required. Feedback will be given on brief outline of plans (formative assessment only) and groups are encouraged to seek feedback and discussion during labs and using online tools on QUT Blackboard. Summary comments and marks are made available to each group once the project has been marked. This item therefore contains strong formative aspects in addition to its summative role. Due Date: Proposal in Week 6; and Final Report in Week 12.
Relates to objectives: All.
Weight: 20%
Internal or external: Internal
Group or individual: Group
Due date: Weeks 6 and 13

Assessment name: Examination (Theory)
Description: (Summative) The end of semester exam will assess your ability to use techniques and principles in applications. Use of a computer package can be examined by asking you to use given computer output to answer questions. Any calculator may be used, and you will be able to take your own personal summaries and written comments into the exam.
Relates to objectives: All.
Weight: 45%
Internal or external: Internal
Group or individual: Individual
Due date: Exam Period

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

All lecture, workshop and practical materials will be available throughout the semester on Blackboard. Lecture notes will be placed on Blackboard before lectures, and may be augmented after lectures to take account of questions or extra comments or examples.

Texts:
1. MacGillivray (2011) Utts and Heckard's Mind on Statistics, Cengage Learning Australia

This text is strongly recommended for support of lecture notes and supplementary reading, examples and exercises. References to it will be supplied in lecture notes.

References:
2. Fawcett & Kent, Statistical Tables
3. Vardeman & Jobe (2001) Basic Engineering Data Collection and Analysis, Cengage
4. MacGillivray & Hayes, Practical Development of Statistical Skills: A Project-Based Approach, QUT Bookshop

Risk assessment statement

There are no out of the ordinary risks associated with this unit since lectures and workshops are held in ordinary lecture theatres or computer laboratories. Basic safety procedures in computer laboratories will be given to you when entering the computer laboratory for the first time. In addition, emergency exits and assembly areas will be pointed out in the first few lectures. You are referred to the university's health and safety web site http://www.hrd.qut.edu.au/healthsafety/healthsafe/index.jsp for further information.

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: 20-Mar-2013