Introduction
The unit has two major topic streams: computational techniques and probability and statistics. Probability and Statistics. An important aspect of engineering is the study, evaluation, and management of the reliability of systems, where reliability is defined as the ability of a system or a component to perform its required functions under stated conditions for a specified period. Reliability can be measured as a probability of failure, frequency of failures, or in terms of system availability. In this part of the unit we will give an introduction on statistics and the theory of probability, then concentrate on techniques of statistical analysis that are useful in engineering environments. Computational Techniques. The use of computers is ubiquitous in modern engineering with enormous faith put in the accuracy of their computations – is that faith founded? In this part of the unit we will explore fundamental numerical processes for obtaining approximate but useful solutions to mathematical models and operations. The consequence of adopting such approximations will be investigated through the evolution and propagation of errors. Statistical and numerical principles will be demonstrated and explored with scientific software including R and Matlab.
Summary
| Unit name | Engineering Mathematics 2B |
| Unit code | KME272 |
| Credit points | 12.5 |
| College/School | Sciences and Engineering School of Natural Sciences |
| Discipline | Mathematics |
| Coordinator | Doctor Michael Brideson |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Intermediate |
Availability
Specific information on 2027 unit availability will be available in August
Learning Outcomes
- calculate probabilities and expectations of combinations of events
- explain appropriate standard probability distributions to model discrete and continuous processes
- make statistically valid inferences, such as hypothesis testing, about observed data
- design and run code to solve problems numerically
- develop appropriate numerical schemes to approximate mathematical models or operations
- assess the evolution and propagation of errors in a numerical approximation scheme
Fee Information
2027 fee information will be available in August.
Requisites
Prerequisites
KMA154Teaching
| Teaching Pattern | 3 x 1-hr workshops weekly, 1 x 2-hr tutorial weekly |
|---|---|
| Assessment | Matlab Grader Assignment (6%)|Probability and Statistics Quiz (10%)|Computational Techniques Tests (20%)|Probability and Statistics Assignments (20%)|Probability and Statistics Test (20%)|Computational Techniques Assignments (24%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
There is no required textbook. Lecture notes will be provided. |
|---|---|
| Recommended | Probability and Statistics Kreyszig is an excellent reference book, covering a broad range of topics including linear algebra, vector calculus, differential equations (ordinary and partial), Fourier analysis, complex analysis, numerical methods, optimisation, and probability and statistics. |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.