1996 Swinburne Higher Education Handbook

Recommended reading
Ferguson, G.A. Statistical Analysis in Psychology &Education. 5th
edn, New York, McGraw Hill, 1981
Norusis, M. SPSS-X. Introductory Statistics Guide. Chicago, Ill.,
SPSS Inc, l990
Norusis, M. SPSS/PC+ Studentware Plus. Chicago, Ill., SPSS Inc.,
1991
Pedhazur, E.]. Multiple Regression in Behavioural Research. 2nd
edn, New York, Holt Rinehart and Winston, 1982
Roscoe, J.T. Fudmental Research for the Behavioural Sciences. 2nd
edn, New York, Holt Rinehart and Winston, 1975
SM378L Design and Measurement 3
4 hours per week Lilydale Prerequisite SM278
Assessment: class work, examination
A stage three subject in the Bachelor of Business and
Bachelor of Social Science
Objectives
-. U-
To extend topics in SM278 to cover a wider variety of
2 statistical techniques.
The emphasis is on understanding how statistical analysis
E.
e; can provide answers to research questions.
Contents
Simple linear regression;
multiple regression;
analysis of covariance;
factor Analysis.
Recommended reading
Francis, G, J. and Taffe J. SM378 Studying Relationships
Francis, G, J. SM378 Analysis of Covariance and Faccor Analysis
Norusis, M, J. SPSS Introductory Statistics Guide, Chicago, Illinois,
SPSS, Inc, 1987
Statistical package:
SPSS for Windows, SPSS Inc., 1994
SM383 Mathematics 2
10 credit points 3 hours per week Hawthorn/Mooroolbark
Prerequisite: SM180 Assessment: tests, examinations and
assignments
A second year subject in the Bachelor of Applied Science
(Mathematics and Computer Science) and (Management
Science and Computing)
Objectives
To provide students with mathematical knowledge and
skills essential for concurrent and later studies;
To enable students with ability and interest further to
develop their mathematical knowledge and skills;
To reinforce and develop mathematical communication
skills and problem solving skills;
To provide students withadditional mathematical
understanding and background material which may be
required;
To demonstrate where mathematics can be applied to
practical situations.
Content
Ordinary differential equations of standard types; numerical
methods of solution; difference equations; simple partial
differential equations. Spaces of vectors and linear equations;
rank, nullspace and range of a matrix. Eigenvalues and
eigenvectors; diagonalistion of simple matrices, applications.
Infinite sequences; infinite series, tests for convergence.
Power series; Taylor and Maclaurin series.
Functions of several variables: linear and quadratic
approximations; stationary points; Taylor polynomials.
SM387 Introduction to Optimisation
10 credit points 3 hours per week Hawthorn/Mooroolbark
Prerequisites: nil Assessment: assignments and examination
A second year subject in the Bachelor of Applied Science
(Mathematics and Computer Science) and (Management
Science and Computing)
Objectives
This subject aims to enable students to:
formulate and solve large linear programming
problems;
perform sensitivity analysis on the solution to linear
programming problems;
formulate and solve integer programming problems;
formulate and solve linear programming transportation
and assignment problems;
formulate and solve problems using dynamic
programming.
Content
Linear and integer programming, simplex method,
sensitivity analysis, transportation and assignment
algorithms, branch and bound methods, deterministic
dynamic programming.
Computer packages such as SAS/OR, Lotus 123/PROPS
may be used.
Recommended reading
Journal of the Operational Research Society
Ravindran, A., Phillips, D.T. and Solberg, J.J., Operations
Research, Principles and Practice. 2nd edn, New York, Wiley, 1987
Winston, W.L., Operations Research: Applications and Algorithms.
3rd edn, Belrnont, Calif., Wadsworth, 1994
SM388 Forecasting and Regression
10 credit points 3 hours per week Hawthorn/Mooroolbark
Prerequisites: SM185, W288 Assessment: tests/examination
and assignments
A second year subject in the Bachelor of Applied Science
(Mathematics and Computer Science) and (Management
Science and Computing)
Objectives
Introduce students to time series forecasting and provide
students with an introduction to different methodologies
and computer packages;
Introduce students to the method and applications of
regression;
Help students tackle real problems;