Page 60 - handbook 20162017

Faculty of Science Handbook, Session 2016/2017

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

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