Page 57 - tmp
P. 57

Faculty of Science Handbook, Session 2017/2018



               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.  Ross,  S.  M.  (2002)  Simulation,  Third  Edition,
               functions.                                          Academic press.
                                                                2.  Roberts,  C.P.  &  Casella,  G.  (1999)  Monte  Carlo
               Assessment:                                         Statistical Methods, Springer.
               Continuous Assessment:       40%                 3.  Dagpunar,  J.  S.  (2007)  Simulation  and  Monte  Carlo,
               Final Examination:           60%                    Wiley.
                                                                4.  Gentle,  J.  E.,  Härdle,  W.  K.  &  Mori,  Y.  (2012)
               Medium of Instruction:                              Handbook  of  Computational  Statistics:  Concepts  and
               English                                             Methods, Springer.
               Humanity Skill:
               CS3, CT3, TS2, LL2




                                                            55
   52   53   54   55   56   57   58   59   60   61   62