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Faculty of Science Handbook, Session 2017/2018

SIT3004 APPLIED STOCHASTIC PROCESSES 6. Bowerman, B.L., O'Connel, R.T., Boehler, A.B. (2005)
Forecasting, Time Series and Regression, Duxbury.
Time reversible Markov chains. Poisson processes.
Continuous-time Markov chains and birth and death
processes. Brownian motion. Application to real-world SIT3006 FURTHER TOPICS IN REGRESSION
phenomena, such as in finance. ANALYSIS
Assessment: Multiple Linear Regression Model: Simultaneous Inference,
Continuous Assessment: 40% criteria for selecting model, influence diagnostics and multi-
Final Examination: 60% collinearity. Introduction to logistic regression and Poisson
regression: maximum likelihood estimates of the
Medium of Instruction: parameters, lack of fit test, tests based on deviance and
English score.
Humanity Skill: Assessment:
CS3, CT3, LL2 Continuous Assessment: 40%
Final Examination: 60%
References:
1. Ross, S. M. (2003). An introduction to probability Medium of Instruction:
models, Eighth Edition, Academic press. English
2. Kao, E. P. C. (1997.) An introduction to stochastic
processes, Duxbury Press. Humanity Skill:
3. Ross, S. M. (1996). Stochastic processes, Second CS2, CT2, LL3
Edition, John Wiley.
4. Durrett, R. (2012). Essentials of stochastic processes, References:
Second Edition, Springer. 1. S. Weisberg (2005). Applied Linear Regression, 3 rd
Ed., Wiley
2. A. Agresti (2013). Categorical data analysis, 3 rd Ed.
SIT3005 TIME SERIES AND FORECASTING METHODS Wiley.
3. P. McCullagh& J.A. Nelder, (1989). Generalized Linear
nd
Introduction to time series: data, properties, examples. Models, 2 Ed, Chapman& Hall.
4. R.H. Myers (1990) Classical and Modern Regression
Introduction to forecasting: Forecasting methods, errors in with applications, Second Edition. Duxbury/Thompson.
forecasting, choosing a forecasting techniques, qualitative 5. R.R. Hocking (2013). Method and Applications of
and quantitative forecasting techniques. Linear Models: Regression and the analysis of
rd
variance, 3 Ed. Wiley.
Time series regression: Modelling trend, detecting
autocorrelation, type of seasonal variation, modelling
seasonal variation, growth curve models, handling first- SIT3007 DATA ANALYSIS II
order autocorrelation
Introduction to different kind of data; Generalizing the linear
Averaging methods: Moving average, Simple exponential regression models including nonlinear regression model,
smoothing, tracking signals, Holt’s method, Holt-Winters Linear regression in time series data, logistic regression
Methods, damped trend exponential method. and Poisson regression models for categorical response
data and selected topics
Box-Jenkins Methods: Stationary data and non-stationary
data, difference, autocorrelation function and partial Practical survey sampling: Selected case study, design of
autocorrelation functions, non-seasonal modeling (ARIMA), study, questionnaires, collecting data, data analysis, oral
diagnostic checking, forecasting. and written presentation
ARCH and GARCH models. Statistical consulting: Theoretical and practical aspects of
statistical consulting, Communication skill
Assessment: Report writing
Continuous Assessment: 40%
Final Examination: 60% Assessment:
Continuous Assessment: 50%
Medium of Instruction: Final Examination: 50%
English
Medium of Instruction:
Humanity Skill: English
CS3, CT3, LL2
Humanity Skill:
References: CS4, CT3, TS5
1. Brockwell, P.J. and Davis, R. A. (2002). Introduction to
Time Series Analysis and Forecasting, 2 nd edition. References:
Springer. 1. S-Plus 2000 Guide to Statistics Volume 1 and II,
2. Montgomery, D. C., Jennings, C. L. and Kulahci, M. Mathsoft corporation.
(2008) Introduction to Time Series Analysis and 2. Cramer, D. (2003) Advanced Quantitative Data
Forecasting. Analysis. Open University Press.
3. Box, G.E.P., Jenkins, G.W., and Reinsel, G. (1994) 3. Evans, J.R. and Olson, D.L. (2007) Statistics, Data
Time series analysis, forecasting and control, 3 rd Analysis, and Decision Modeling. Prentice Hall
edition. Prentice Hall. 4. Miller, D.C. and Salkind, J. (1983) Handbook of
4. Makridakis, S., Wheelwright, S.C., Hyndman, R.J. Research Design and Social measurements. Sage
(1998) Forecasting Methods and Application, Wiley. Publication.
5. Lazim, M.A. (2001) Introductory Business Forecasting, 5. Derr, J. (2000) Statistical Consulting: A guide to
A practical approach, Univision Press. effective communication, Pacific Grove: Duxbury.

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