Page 123 - handbook 20152016

Faculty of Science Handbook, Session 2015/2016

3. Ewens, W.J. & Grant, G.R. (2005). Statistical Methods posterior sampling. Bayesian decision theory. Application to
in Bioinformatics: An Introduction (2nd ed.). New York: real-world problems.
Springer.
4. Pevsner, J. (2009). Bioinformatics and Functional Assessment:
Genomics (2nd ed.). New York: Wiley-Blackwell. Continuous Assessment: 40%
Final Examination : 60%

SIT3012 DESIGN AND ANALYSIS OF EXPERIMENTS Medium of Instruction:
English
Philosophy related to statistical designed experiments.
Analysis of variance. Experiments with Blocking factors. Humanity Skill:
Factorial experiments. Two level factorial designs. Blocking CS3, CT3, TS2, LL2
and confounding system for two-level factorials. Two-level
fractional factorial designs. References:
1. Lee, P. M. (1991) Bayesian statistics: an introduction.
Assessment: Oxford University Press.
Continuous Assessment: 40% 2. Hoff, P. D. (2009) A first course in Bayesian statistical
Final Examination: 60% methods. Springer.
3. Koch, K. (2007) Introduction to Bayesian statistics,
Medium of Instruction: Second Edition, Springer.
English 4. Cowles, M. K. (2013) Applied Bayesian statistics:
with R and OpenBUGS examples, Springer.
Humanity Skill:
CT4, TS1, LL2
SIT3015 JAVA METHODS FOR STATISTICS AND
References: ACTUARIAL SCIENCE
1. Montgomery, D.C.: Design and Analysis of
Experiments. 6th edition, John Wiley, 2004. JAVA programming language: Object, class and method.
2. Box, G.E.P., Hunter, W.G. and Hunter,J.S.: Statistics Sample java programs which make use of Java methods to
for Experimenters. 2nd edition, John Wiley, 2005.
3. Tabachnick, B.G., Fidell, L.S.: Experimental designs 1. Perform data manipulation, matrix operations and
nonlinear optimization.
using anova, Duxbury, 2007. 2. Perform computation and simulations in Brownian
4. Myers, R.H.: Classical and Modern Regression motion models, Levy processes, CIR model and other
Analysis with Applications. 2nd edition, Duxbury, 1990 models.
3. Find the premiums of investment-linked insurance
policies.
SIT3013 ANALYSIS OF FAILURE AND SURVIVAL 4. Find approximately aggregate claims distribution and
DATA ruin probabilities.
5. Find provision of risk margin for adverse deviation
Survival distributions, hazard models. Reliability of (PRAD) of claim liabilities for general insurance
systems, stochastic models. Censoring and life-tables. The business.
product-limit estimator. Parametric survival models under
censoring. Cox proportional hazards model and other basic Assessment:
models with covariates. Continuous Assessment: 40%
Final Examination: 60%
Assessment:
Continuous Assessment: 40% Medium of Instruction:
Final Examination: 60% English

Medium of Instruction: Humanity Skill:
English CS2, CT2, LL1

Humanity Skill: References:
CS1, CT2, LL1 1. Philip Barker (2007), Java Methods for Financial
Engineering, Applications in Finance and Investment,
References: Springer-Verlag London Limited.
1. Sherwin D.J. and Bossche A. (2012), The Reliability, 2. Everitt, B. S. Introduction to Optimization Methods and
Availability and Productiveness of Systems, Springer Their Application in Statistics, Chapman and Hall.
Netherlands. 3. Deitel, H. M. & Deitel, P. J. (1995), Java How to
2. Peter J. Smith (2002). Analysis of Failure and Survival Program, Prentice-Hall.
Data. Chapman & Hall. 4. Hurbbard, John R. (2004), Programming with JAVA
3. Tableman M. & Kim J.S. (2004). Survival Analysis (Schaum's Outline Series), McGraw- Hill International
using S - Analysis of Time-to-Event Data. Chapman & Editions.
Hall.
4. Smith D.J. (2011) Reliability Maintainability and Risk,
th
Practical Methods for Engineers, 8 Ed., Elsevier Ltd.

SIT3014 INTRODUCTION TO BAYESIAN
STATISTICS

Bayes' Theorem. Bayesian framework and terminology.
Bayesian inference. Prior formulation. Implementation via

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