1997 Swinburne Higher Education Handbook

Collins, 1994
Kolb, D.A., Rubin I.M., and Oslund, J., Organizational
Behaviour: An Experiential Approach, New York, Prentice Hall,
1991
Meredith, J.R. and Mantel, S.J. Project Management: A Managerial
Approach, New York, Wiley, 1995
Quinn, R.E., Faerman, S.R., Thompson, M.P., and MCGrath,
M.R., Becoming a Master Manager - A Competency Framework,
New York, Wiley, 1990
Rosenweig, B., Ziegler, M. and Ziegler, P., The Republic of Tea:
Letters to a Young Zentrepreneur New York, Doubleday, 1993
Zachary, G., Pascal Showstopper! The Breakneck Race to Create
Windows NTand the Next Generation at Microsoft New York, The
Free Press, 1994
SM484
Experimental Design and Multiple
Regression
10 credit points 3 hours per week Hawthorn Prerequisite:
94388 Assessment: tests/examinution and assignments
A second year subject in the Bachelor of Applied Science
(Mathematics and Computer Science).
Objectives
To introduce the concepts and methods of experimental
design;
Analyse designed experiments using the Analysis of
Variance;
Extend the method of regression to multiple linear
regression.
Content
Inference for two independent groups. The F Test.
The analysis of variance for single-factor completely
randomised designs, randomised blocks, and two-factor
equally replicated designs.
Non-parametric methods. Planned and unplanned
comparisons.
Design of experiments, blocking, the 2" and fractional 2"
designs.
Multiple Linear Regression: the linear model with several
predictors.
Assumptions for ordinary least squares, methods for
checking the assumptions, including normal probability
plots, residual plots, the lack-of-fit test and the Durbin-
Watson test for autocorrelation; outliers.
Computer packages such as Minitab and SAS will be used.
Recommended reading
Brook, R.J. and Arnold, G.C., Applied Regression Analysis and
Experimental Design. New York, Dekker, 1985
Dunn, O.J. and Clark, V.A. Applied Statistics: Analysis of Variance
and Regression. 2nd edn, New York, Wiley, 1987
Groeneveld, R.A., Introductory Statistical Methods. Boston, PWS-
Kent, 1988
Mendenhall, W. and McClave, J.T., A Second Course in Business
Statistics: Regression Analysis. 4th edn, San Francisco, Calif.,
Dellen, 1990
Wonnacott, T.H. and Wonnacott, R.J., Regression: A Second
Course in Statistics. Malabar, Fla., Krieger, 1986
SM487 Queueing Theory and Simulation
10 credit points 3 hours per week Hawthom Prerequisites:
SM18S. Assessment: assignments and examination
A third year subject in the Bachelor of Applied Science
(Mathematics and Computer Science)
0 b jectives
Develop analytical models of queues forming under
different conditions.
Apply queueing models to real stituations.
Model problems in queues and inventory using
simulation methods.
Content
Queueing theory, simulation, applications to computers,
inventory models and scheduling.
Computer packages such as Lotus 123/PROPS and SAS,
SAS/OR and ARENA 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, Belmont, Calif., Wadswonh, 1994
SM493 Engineering Mathematics
4 credit points 2 hours per week Hawthom Prerequisites:
W 9 3 Assessment: examination, tests and assignments
A fourth year subject in the Bachelor of Engineering
(Mechanical)
Objectives
To introduce the mathematical concepts of approximation
and the finite element method.
Content
Concepts of finite element methods; approximation, basis
functions, quadrature, weighted residual methods, ordinary
and partial differential equations.
Recommended reading
Davies, A.J., The Finite Element Method. A First Approach. Oxford,
Oxford University Press, 1980
Easton, A.K., Robb, P.J. and Singh, M., Approximation and the Finite
Element Method 1995
SM494 Engineering Mathematics
4 credit points 2 hours per week Prerequisite: 94394
Engineen'ng Mathematics Instruction: lectures/tutods
Assessment: examination/tutorial assignment
A fourth year subject in the Bachelor of Engineering
(Electrical).
0 bjectives
To further develop the specialised mathematical analytical
techniques used in the more advanced and specialised
engineering subjects.
Content
Complex variables: elementary functions, geometry of the
complex plane, mappings, complex differentiation,