Page 175 - FINAL_HANDBOOK_20242025

Faculty of Science Handbook, Academic Session 2024/2025

Assessment:
Assessment: Continuous Assessment: 40%
Continuous Assessment:100% Final Examination: 60%

SIT3003
COMPUTER INTENSIVE SIT3005
METHODS IN STATISTICS TIME SERIES AND
FORECASTING METHODS
Computer generation of
uniform and non-uniform Introduction to time series and
random variables. Monte Carlo forecasting. Time series
evaluation of integrals. graphics. Simple forecasting
Variance reduction techniques. methods. Transformation and
Bootstrap and jackknife adjustments. Fitted values,
methods; Applications in residuals and prediction
confidence interval intervals. Time series
construction. Maximum regression. Time series
likelihood estimation of model decomposition. Exponential
parameters via the smoothing. ARIMA models.
Expectation-Maximization (EM) ARCH and GARCH models.
algorithm. The Markov Chain
Monte Carlo method. Assessment:
Continuous Assessment: 40%
Assessment: Final Examination: 60%
Continuous Assessment: 40%
Final Examination: 60%
SIT3008
INTRODUCTION TO SURVEY
SIT3004 SAMPLING
APPLIED STOCHASTIC
PROCESSES This course focuses on
statistical sampling methods
Time reversible Markov chains. with applications in the analysis
Poisson processes. of sample survey data. The
Continuous-time Markov sampling methods include
chains and birth and death simple random sampling,
processes. Brownian motion. stratified random sampling,
Application to real-world systematic sampling and
phenomena, such as in cluster sampling. Estimation of
finance. population parameters for
different sampling methods will
be fully discussed. Special

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