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# Engineering computations and probability

### Available in 2013

Callaghan Campus Semester 2

### Previously offered in 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004

The aim of this course is to introduce the principles of engineering computations and probability and statistics. Its purpose is to provide foundation material for later year courses in water, structural and geotechnical engineering.

Objectives The course objectives are:

A1: To understand and implement some basic numerical algorithms for computing solutions of single nonlinear equations and systems of linear equations.

A2: To understand and implement algorithms for interpolation, curve fitting, numerical differentiation, and numerical integration.

A3: To understand and implement numerical methods for solving ordinary differential equations, as well as elliptic and parabolic partial differential equations.

A4: Understand the key concepts of probability and Bayesian inference.

A5: Formulate and solve problems dealing with probability and statistics in civil and environmental engineering applications.

A6: Develop practical skill in Monte Carlo simulation.
Content The content of the course includes:

1. The numerical solution of a single nonlinear equation, systems of linear equations, ordinary differential equations, and partial differential equations.

2. The numerical implementation of interpolation and curve fitting.

3. An introduction to probability and distribution theory targetted to civil and environmental engineering applications.

4. Monte Carlo simulation: theory and practice.

5. Introduction to Bayesian statistical inference with applications to the binomial and linear regression models.
Replacing Course(s) N/A.
Transition N/A.
Industrial Experience 0
Assumed Knowledge Content covered in course GENG1002 Introduction to Engineering Computations, and content covered in course MATH1120 Mathematics 2.
Modes of Delivery Internal Mode
Teaching Methods Lecture
Tutorial
Assessment Items
Examination: Formal NOTE: Any modification to the above assessment arrangement will appear on the course outline normally issued in Week 1. Computational Methods: Progressive assessment. Probability and Statistics: Progressive assessment.
Contact Hours Lecture: for 4 hour(s) per Week for Full Term
Tutorial: for 2 hour(s) per Week for Full Term
Timetables 2013 Course Timetables for CIVL2050
• Last Updated: Wednesday, 24 April 2013 9:24 AM AEST