This subject develops students' practical skills by using computer software to solve mathematical applications. The two main applications considered are the numerical solutions of differential equations (ordinary and partial); and fitting data to a model using least-squares regression (linear and non-linear).

Session 2 (60)

Online

Wagga Wagga Campus

HD/FL

One session

School of Computing and Mathematics

MTH220

- be able to write computer programs to solve real-life problems;
- be able to numerically calculate the solutions of ordinary differential equations using various methods;
- be able to adapt existing code to produce numerical solutions for differential equations;
- be able to generate suitable finite difference equations from differential equations;
- be able to determine the stability of a finite difference equation;
- be able to calculate the solutions of partial differential equations using various methods;
- be able to fit data to a model using linear and non-linear regression techniques;
- be able to interpret mathematical models and communicate their output to non-mathematical audiences.

- Introduction to mathematical modelling.
- Programming with Maple.
- Linear regression: simple and multiple; forward selection and backwards elimination methods.
- Numerical solution of ordinary differential equations for both initial and boundary value problems; Euler's method, Runge-Kutta method, shooting method and finite difference methods.
- Fourier series.
- Partial differential equations (parabolic, hyperbolic and elliptic): separation of variables, numerical solution using finite difference methods; stability of finite difference methods and method of characteristics.
- Non-linear regression: various numerical methods: grid, gradient, Gauss-Newton and mixed.

*The information contained in the CSU Handbook was accurate at the date of publication: January 2020. The University reserves the right to vary the information at any time without notice.*