Page 155 - buku panduan 20192020

Faculty of Science Handbook, Session 2019/2020

Assessment: collinearity. Introduction to logistic regression and Poisson
Continuous Assessment: 40% regression: maximum likelihood estimates of the
Final Examination: 60% parameters, lack of fit test, tests based on deviance and
score.
Medium of Instruction: Assessment:
English Continuous Assessment: 40%
Final Examination: 60%
Soft Skills:
CS3, CTPS3 Medium of Instruction:
English
References:
1. Ross, S. M. (2003). An introduction to probability Soft Skills:
th
models (8 ed.). Academic press. CS2, CTPS2
2. Kao, E. P. C. (1997.) An introduction to stochastic
processes. Duxbury Press. References:
3. Ross, S. M. (1996). Stochastic processes (2 ed.). 1. S. Weisberg (2005). Applied linear regression (3 ed.).
nd
rd
John Wiley. Wiley.
rd
4. Durrett, R. (2012). Essentials of stochastic processes 2. A. Agresti (2013). Categorical data analysis (3 ed.).
nd
(2 ed.). Springer. Wiley.
3. P. McCullagh, & J. A. Nelder. (1989). Generalized
nd
linear models (2 ed.). Chapman& Hall.
SIT3005 TIME SERIES AND FORECASTING METHODS 4. R. H. Myers. (1990). Classical and modern regression
nd
with applications (2 ed.). Duxbury/Thompson.
Introduction to time series: data, properties, examples. 5. R. R. Hocking. (2013). Method and applications of
linear models: Regression and the analysis of variance
rd
Introduction to forecasting: Forecasting methods, errors in (3 ed.). Wiley.
forecasting, choosing a forecasting techniques, qualitative
and quantitative forecasting techniques. SIT3007 DATA ANALYSIS II

Time series regression: Modelling trend, detecting Introduction to different kind of data; Generalizing the linear
autocorrelation, type of seasonal variation, modelling regression models including nonlinear regression model,
seasonal variation, growth curve models, handling first- Linear regression in time series data, logistic regression
order autocorrelation and Poisson regression models for categorical response
data and selected topics
Averaging methods: Moving average, Simple exponential
smoothing, tracking signals, Holt’s method, Holt-Winters Practical survey sampling: Selected case study, design of
Methods, damped trend exponential method. study, questionnaires, collecting data, data analysis, oral
and written presentation
Box-Jenkins Methods: Stationary data and non-stationary Statistical consulting: Theoretical and practical aspects of
data, difference, autocorrelation function and partial statistical consulting, Communication skill
autocorrelation functions, non-seasonal modeling (ARIMA), Report writing
diagnostic checking, forecasting.
ARCH and GARCH models. Assessment:
Continuous Assessment: 50%
Assessment: Final Examination: 50%
Continuous Assessment: 40%
Final Examination: 60% Medium of Instruction:
English
Medium of Instruction:
English Soft Skills:
CS4, CTPS3, TS5
Soft Skills:
CS3, CTPS3 References:
1. S-Plus 2000 guide to statistics (Vols. 1-2). Mathsoft
References: corporation.
1. Hyndman, R.J., & Athanasopoulus, G. (2014). 2. Cramer, D. (2003). Advanced quantitative data
Forecasting: principles and practice. Retrieved from analysis. Open University Press.
https://www.otexts.org/fpp 3. Evans, J.R., & Olson, D.L. (2007). Statistics, data
2. Makridakis, S., Wheelwright, S.C., & Hyndman, R.J. analysis, and decision modeling. Prentice Hall
(1998). Forecasting methods and applications. Wiley. 4. Miller, D.C., & Salkind, J. (1983). Handbook of
3. Montgomery, D. C., Jennings, C. L., & Kulahci, M. research design and social measurements. Sage
(2008). Introduction to time series analysis and Publication.
forecasting. Wiley. 5. Derr, J. (2000). Statistical consulting: A guide to
4. Brockwell, P.J., & Davis, R. A. (2002). Introduction to effective communication. Pacific Grove: Duxbury.
time series analysis and forecasting (2 ed.). Springer. 6. Jarman, Kristin H. (2013). Art of data analysis: How to
nd
5. Box, G.E.P., Jenkins, G.W., & Reinsel, G. (1994). Answer almost any question using basic statistics.
rd
Time series analysis, forecasting and control (3 ed.). John Wiley & Sons
Prentice Hall.

SIT3008 INTRODUCTION TO SURVEY SAMPLING
SIT3006 FURTHER TOPICS IN REGRESSION
ANALYSIS Techniques of statistical sampling with applications in the
analysis of sample survey data. Topics include simple
Multiple Linear Regression Model: Simultaneous Inference, random sampling, stratified sampling, systematic sampling,
criteria for selecting model, influence diagnostics and multi-

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