units

MAT2003

Faculty of Information Technology

# Undergraduate - UnitMAT2003 - Continuous mathematics for computer science

This unit entry is for students who completed this unit in 2015 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study. print version

## 6 points, SCA Band 2, 0.125 EFTSL

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

 Level Undergraduate Faculty Faculty of Information Technology Offered Clayton Second semester 2015 (Day)Malaysia Second semester 2015 (Day)Malaysia October intake 2015 (Day) Coordinator(s) Dr Jennifer Flegg (Clayton); Associate Professor Lan Boon Leong (Malaysia)

### Synopsis

Probability and combinatorics: elementary probability theory, random variables, probability distributions, expected value; counting arguments in combinatorics; statistics. Linear algebra: vectors and matrices, matrix algebra with applications to flow problems and Markov chains; matrix inversion methods. Calculus: differentiation and partial differentiation; constructing Taylor series expansions.

### Outcomes

On successful completion of this unit, students should be able to:

1. apply counting principles in combinatorics and derive key combinatorial identities;
2. describe the principles of elementary probability theory, evaluate conditional probabilities and use Bayes' Theorem;
3. recognise some standard probability density functions, calculate their mean, variance and standard deviation, demonstrate their properties and apply them to relevant problems;
4. implement the principles of experimental design based on those probability density functions, and apply confidence intervals to sample statistics;
5. demonstrate basic knowledge and skills of linear algebra, including to manipulate matrices, solve linear systems, and evaluate and apply determinants;
6. apply knowledge of linear algebra to relevant problems, such as network flow and Markov chains;
7. describe fundamental knowledge of calculus including to differentiate basic, composite, inverse and parametric functions;
8. calculate approximations of functions with tangent lines, evaluate power series and construct Taylor series;
9. perform key skills in the calculus of functions of several variables including to calculate partial derivatives, find tangent planes, identify stationary points and construct Taylor series.

### Assessment

Examination (3 hours): 70%; In-semester assessment: 30%

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

• Three hours of lectures
• One 1-hour laboratory

• A minimum of 8 hours independent study per week for completing lab and project work, private study and revision. 