Please note - Swinburne University of Technology

SM735
Survey Sampling
12.5 credit points
No. of hours per week: four hours
Subject aims and description
This subject aims to introduce the theory and practice of
sampling methods for social surveys. The emphasis is on basic
sampling methods such as simple random sampling, stratified
sampling and cluster sampling, and includes the estimation of
standard errors.
Textbooks and References
To be advised.
SM741
Statistics and Reliability
No. of hours per week: two hours
Subject description
Frequency distributions; mean, median, mode, measures of
dispersion. Probability. Probability distributions; biomial,
normal, Poisson and Weibull. Tests of hypothesis and
significance. Reliability mathematics; meantime between
failures, failure rates, mortality curves, cumulative probability
distributions. Boolean algebra and introduction to Fault Free
applications. Review of applicable computational techniques.
-. 0 References
. Bajpai, A.C., Calus, I.M., Fairley, J.A. Statistical Methods for Engineers
g.
and Scientists: A Student's Course Book. Chichester, Sussex, Wiley,
- 1978
O'Connor, P.D.T. Practical Reliability Engineering. 2nd edn, Chichester,
Wiley, 1985
Rade, L. and Westergren, B. BetaMathematics Handbook. 2nd edn,
Lund, Studentlitteratur, 1990
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2. ,-n ~ ~ 7 4 2 Elementary Statistical Modelling
12.5 credit points
No. of hours per week: four hours
Prerequisites: SM750, SM751
Subject aims description
This subject aims to extend the work done in lntroduction to
- Data Analysis by further developing the concepts of statistical
estimation and testing. Topics will include analysis of variance
and regression. lntroduction to multiple regression.
lntroduction to analysis of categorical data.
Textbooks and References
To be advised.
SM743 Multivariate Statistics 1
12.5 credit points
No. of hours per week: four hours
Prerequisite: SM742
Subject aims and description
This subject aims to identify and apply the multivariate
techniques most commonly used in social research and to
understand the assumptions underlying their use. The course
will include a selection of tooics chosen from multiole
regression, statistical infererice for multivariate data, principal
component analysis, factor analysis, discriminant analysis and
cluster analysis.
Textbooks and References
To be advised.
SM744
Statistical Modelling
12.5 credit points
No. of hours per week: four hours
Prerequisite: SM743
Subject aims and description
This subject aims to make an in-depth study of several
statistical modelling techniques for both categorical and
higher level data. Topics will be chosen from: regression
models for categorical data: log-linear models for multiway
contigency tables, logistic regression for analysing binary
response data. Causal modelling, structural equation models,
LISREL.
Textbooks and References
To be advised.
5~745 Project Planning
12.5 credit points
No. of hours per week: four hours
Prerequisites: Requirements of the Graduate
Diploma in Social Statistics with at least two
distinctions in the second year
Subject aims and description
In this subject students define and plan a project and conduct
an extensive literature search. The content will vary from
student to student depending on the work undertaken. It will
involve selecting an appropriate project and conducting an
extensive literature search.
Textbooks and References
Depends on topic.
~ ~ 7 4 6 Multivariate Statistics 2
12.5 credit points
No. of hours per week: four hours
Prerequisite: SM743
Subject aims and description
This subject aims to make an in-depth study of a range of
multivariate techniques used in social research. A selection of
topics will be made from multivariate analysis of variance,
multiple regression, factor analysis, discriminant analysis,
cluster analysis, conjoint analysis, correspondence analysis and
scaling techniques such as multi-dimensional scaling.
Textbooks and References
To be advised.
S~747 Secondary Data Analysis
12.5 credit points
No. of hours per week: four hours
Prerequisite: SM733
(This subject is not offered every year)
Subject aims and description
This subject aims to develop the ability to explore complex
datasets with a view to formulate policy decisions. Starting
with existing datasets investigate policy formulation problems
making use of the techniques learnt elsewhere in the course.
Textbooks and References
To be advised.