Page 59 - handbook 20162017

Faculty of Science Handbook, Session 2016/2017

References: References:
1. Tibco Spotfire S-Plus Guide to Statistics Volume 1, 1. Halsey Royden and Patrick Fitzpatrck, Real Analysis,
TIBCO Software Inc. International Edition, 4/E, Pearson, 2010.
2. Mann, Prem. S., (2003). Introductory Statistics, John 2. Robert G. Batle, The Elements of Integration and
Wiley & Sons. Lebesgue Measure, John Wiley, 1995.
3. Siegel, A.W., and Morgan, C.J., (1998). Statistics and 3. R.M. Dudley, Real Analysis and Probability,
Data Analysis, John Wiley & Sons. Cambridge University Press, 2002.
4. Evans, J.R. and Olson, D.L. (2002)Statistics, Data 4. Taylor, J.C. An Introduction to Measure and Probability
Analysis and Decision Modeling and Student CD- Theory.Springer, 1997.
ROM (2nd Edition), Prentice Hall.

SIT3002 INTRODUCTION TO MULTIVARIATE
SIT2006 NON-PARAMETRIC STATISTICS ANALYSIS
Statistical hypotheses, binomial test, runs test, sign test, The use/application of Multivariate analysis.Managing and
contingency tables, median test, chi-square Goodness of Handling Multivariate data.Matrix theory.Random vectors
Fit test. Some methods based on ranks. and Matrices.Multivariate Normal Distribution.Wishart
distribution and Hotellings distribution. Selected topics from
Assessment: Graphical methods, Regression Analysis, Correlation,
Continuous Assessment: 40% Principle Components, Factor Analysis, Discriminant
Final Examination: 60% analysis and Clustering Methods.
Medium of Instruction: Assessment:
English Continuous Assessment: 40%
Final Examination: 60%
Humanity Skill:
CS2, CT2, TS1, LL2, EM2 Medium of Instruction:
English
References:
1. W.W. Daniel, Applied Nonparametric Statistics, 2nd ed Humanity Skill:
PWS-Kent,1990 CS2, CT3, LL2, EM1
2. J.D.Gibbons, Nonparametric methods for Quantitative
Analysis, American Science Press,Columbus, 1985 References:
3. W.J.Conover, Practical NonParametric Statistics, 1. Johnson, K. A. & Wichern, D. W. (2002), Applied
Wiley,1980 Multivariate Analysis, Prentice-Hall International,
4. M. Kraska-Miller Nonparametric statistics for social (5 ed.).
th
andbehavioral sciences,CRC Press Taylor & Francis 2. C. Chatfield & A. J. Collins (1980), An Introduction to
Group, 2014 Multivariate Analysis, Chapman & Hall.
3. Anderson, T. A. (1984), An Introduction to Multivariate
Statistical Analysis, Wiley (2 ed.).
nd
SIT3001 INTRODUCTION TO PROBABILITY
THEORY
SIT3003 COMPUTER INTENSIVE METHODS IN
An introduction to concepts and fundamentals of measure STATISTICS
theory essential for a rigorous approach to the basics of
probability. Computer generation of uniform and non-uniform random
variables. Monte Carlo evaluation of integrals. Bootstrap
Sequences and series of functions and sets, convergence, and jackknife methods. Variance reduction techniques.
limit infimum and limit supremum. Expectation-Maximization algorithm. Markov Chain Monte
Carlo methods.
Rings and algebras of sets, construction of a measure.
Measurable functions and their properties, Egorov's Assessment:
theorem, convergence in measure. Lebesgue integral, its Continuous Assessment: 40%
elementary properties, integral and sequences, Fubini Final Examination: 60%
theorem. Medium of Instruction:
English
Probability space and measure. Random variables.
Independence. Sums of random variables. Borel-Cantelli Humanity Skill:
Lemma. Convergence in distribution, in probability and CS3, CT3, LL2
almost surely; weak and strong laws of large numbers,
central limit theorem. Law of Iterated Logarithm. Generating References:
functions: characteristic functions, moment generating 1. Roberts, C.P. & Casella, G. (2000). Monte Carlo
functions. Statistical Methods, Springer.
2. Ross, S.M. (1991). A Course In Simulation, Maxwell-
Assessment: Macmillan.
Continuous Assessment: 40%
Final Examination: 60%
SIT3004 APPLIED STOCHASTIC PROCESSES
Medium of Instruction:
English Time reversible Markov chains. Poisson processes.
Continuous-time Markov chains and birth and death
Humanity Skill: processes. Brownian motion. Application to real-world
CS3, CT3, TS2, LL2 phenomena, such as in finance.

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