ENG5001 - Advanced engineering data analysis - 2017

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Engineering

Coordinator(s)

Professor Zixiang Xiong

Unit guides

Offered

Clayton

  • First semester 2017 (Day)

Malaysia

  • First semester 2017 (Day)

Synopsis

The unit consists of a review of probabilistic foundations for data analysis including probability, random variables, expectation, distribution functions, important probability distributions, central limit theorem, random vectors, conditional distributions and random processes.

Students will develop the foundations of statistical inference including estimation, confidence intervals, maximum likelihood, hypothesis testing, least-squares and regression analysis.

A selection of more advanced topics in probability, random modelling and statistical inference will also be presented.

The material will be taught in the context of real engineering problems taken from multiple engineering disciplines. A widely used numerical computing environment will be used extensively throughout the unit.

Outcomes

At the successful completion of this unit you will be able to:

  1. Assess the problem from an engineering perspective but also deliberate on the relevant social, cultural, environmental, legislative, ethical and business factors.
  2. Draw on creative problem-solving methodologies, decision-making and design skills to develop innovative concepts, products, services and solutions.
  3. Justify the use of appropriate computer modelling techniques and experimental methods, whilst ensuring model or test applicability, accuracy and limitations of the methods.
  4. Engage with and lead an effective team and apply industry standard project management tools and practices.
  5. Demonstrate the effective communication of the outcomes in a written and verbal format and assess the work of others.

Assessment

Continuous assessment: 50%

Examination (3 hours): 50%

Students are required to achieve at least 45% in the total continuous assessment component and at least 45% in the final examination component and an overall mark of 50% to achieve a pass grade in the unit. Students failing to achieve this requirement will be given a maximum of 45% in the unit.

Workload requirements

3 hours lectures, 2 hours of labs and 7 hours of private study per week.

See also Unit timetable information

Chief examiner(s)

Prerequisites

None

Co-requisites

None

Prohibitions

None