Page 58 - handbook 20162017
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Faculty of Science Handbook, Session 2016/2017



               Power  of  a  statistical  test.  Best  critical  region.  Likelihood  Humanity Skill:
               ratio   test.   Chebyschev's   inequality.   Rao-Cramer's  CS3, CT3
               inequality.  Convergence  in  probabilityand  distribution.
               Asymptotic distribution of maximum likelihood estimator.  References:
                                                                1.  Lefebvre,  M.  (2007). Applied  Stochastic  Processes,
               Assessment:                                          Springer.
               Continuous Assessment:       40%                 2.  Ross,  S.  M.  (2007). Introduction  to  Probability
               Final Examination:           60%                     Models, 9th edition, Academic Press.
                                                                3.  Chung,  K.  L.  and  Farid  Aitsahlia  (2003)  Elementary
               Medium of Instruction:                               Probability Theory with Stochastic Processes and An
               English                                              Introduction  to  Mathematical  Finance,  4th  edition.
                                                                    Springer.
               Humanity Skill:                                  4.  Jones,  P.  W.  (2001).  Stochastic  Processes:  An
               CS3, CT3, LL2                                        Introduction, Arnold.
                                                                5.  Durrett,  R.  (2012).  Essentials  of  Stochastic
               References:                                          Processes, Springer.
               1.  R.V.  Hogg  &  E.A.  Tanis, Probability  andStatistical
                           th
                   Inference, 8 ed., Prentice Hall, 2014.
               2.  R.V. Hogg & T.C. Craig, Introduction to Mathematical  SIT2004  REGRESSION ANALYSIS
                           th
                   Statistics, 7 ed., Prentice-Hall, 2014.
               3.  D.  Wackerly,  W.  Mendenhall,  R.L.  Scheaffer,  Simple  linear regression:  Estimation,  hypothesis  testing,
                                                      th
                   Mathematical and Statistics with Applications, 7 ed.,  analysis  of  variance,  confidence  intervals,  correlation,  the
                   Thomson, 2008.                              residuals,  prediction.    Model  inadequacies,  diagnostic,
                                                               heterogeneity  of  variance,  nonlinearity,  distributional
                                                               assumption,  outliers,  transformation.  Selected  topics
               SIT2002  FURTHER MATHEMATICAL STATISTICS        matrix  theory  and  multivariate  normal  distribution:  An
                                                               introduction to multiple linear regression.
               The  exponential  family;  sufficient,  complete  and  ancillary
               statistics; Minimum variance unbiased estimators; Sufficient  Assessment:
               statistics  and  best  estimators;  Bayesian  estimation;  Delta  Continuous Assessment:  40%
               method  for  asymptotic  approximation;  Distributions  of  Final Examination:  60%
               special  quadratic  forms;  One  and  two  factors  analysis  of
               variance;  Linear  regression  theory  and  inference  of  Medium of Instruction:
               parameters;  Correlation  analysis  in  bivariate  normal  English
               distribution; Sequential probability ratio test.
                                                               Humanity Skill:
               Assessment:                                     CS2, CT3, LL2, EM1
               Continuous Assessment:       40%
               Final Examination:           60%                References:
                                                                                                      nd
                                                               1. Weisberg S. (1985). Applied Linear Regerssion, 2 ed.,
               Medium of Instruction:                             Wiley.
               English                                         2. Bowerman  B.  L.  &  O'Connel  R.T.  (1990). Linear
                                                                                nd
                                                                  Statistical Models, 2 ed., PWS-Kent.
               Humanity Skill:                                 3. Myers, R.H. & Miltors J.S. (1991). A First Couse in the
               CS3, CT3, TS2, LL2                                 Theory of Linear Statistical Models, PWS-Kent.
                                                               4. Montgomery, D.C., Peck, E. A. (1992). Introduction to
               References:                                        linear regression analysis, Wiley.
               1.  Hogg,  R.V.  &  Craig,  A.T.  (1995).  Introduction  to  5. J.S.  Milton,  J.C.  Arnold  (2004).  Introduction  to
                   Mathematical Statistics (5th ed.). New York: Wiley.  Probability and Statistics, McGraw-Hill.
               2.  Hogg, R. & Tanis, E. (2010). Probability and Statistical
                   Inference (8th ed.). USA: Pearson Education.
               3.  Bickel,  P.J.  &  Doksum,  K.A.  (2001).  Mathematical  SIT2005  DATA ANALYSIS I
                   Statistics: Basic Ideas and Selected Topics, Vol.1 (2nd
                   ed.). Upper Saddle River, NJ: Prentice- Hall.  Statistical  Analysis  for  mean,  variance,  count  and
               4.  Casella, G. & Berger, R.L. (2002). Statistical Inference  proportion:  Hypothesis  testing,  confidence  interval  and
                   (2nd ed.). Pacific Grove, CA: Thompson Learning.  tests of independence.
                                                               Statistical  analysis  for  regression  and  Correlation:
                                                               continuous  response  data,  simple  and  multiple  linear
               SIT2003  STOCHASTIC PROCESSES                   model.
               Definition  and  examples  of  stochastic  processes.  Statistical  tests:  Goodness  of  fit  tests,  ANOVA,
               Introduction to simple random walk. Discrete time Markov  Nonparametric test
               Chains.  Transition  probability.  Properties  of  class.
               Transience   and   recurrence   properties.   Absorbing  Assessment:
               probability.  Stationary  distribution  and  limiting  probability.  Continuous Assessment:  50%
               Some applications.                              Final Examination:           50%
               Assessment:                                     Medium of Instruction:
               Continuous Assessment:       40%                English
               Final Examination:           60%
                                                               Humanity Skill:
               Medium of Instruction:                          CS3, CT3
               English




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