Available in 2017

Course handbook


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.

Availability2017 Course Timetables


  • Winter - 2017
  • Semester 2 - 2017

BCA Singapore

  • Semester 2 - 2017

Learning outcomes

On successful completion of the course students will be able to:

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

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

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

4. Understand the key concepts of probability and Bayesian inference.

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

6. Develop practical skill in Monte Carlo simulation


The content of the course includes:

  1. 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.  

Assumed knowledge

Content covered in course GENG1002 Introduction to Engineering Computations, and content covered in course MATH1120 Mathematics 2.

Assessment items

Written Assignment: Written Assignments

Formal Examination: Formal Examination

Contact hours

BCA Singapore and Callaghan


Face to Face On Campus 4 hour(s) per Week for Full Term


Face to Face On Campus 2 hour(s) per Week for Full Term