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Faculty of Science Handbook, Session 2019/2020


               Soft Skills:
               CS3, CTPS4

               References:
               1.   Montgomery,  D.C.  (2004).  Design  and  analysis  of
                   experiments (6  ed.). John Wiley.
                              th
               2.   Box, G. E. P., Hunter, W. G., & Hunter, J. S. (2005).
                                        nd
                   Statistics for experimenters (2  ed.). John Wiley.
               3.   Tabachnick, B. G., & Fidell, L. S. (2007). Experimental
                   designs using ANOVA. Duxbury.
               4.   Myers, R.H. (1990). Classical and modern regression
                                       nd
                   analysis with applications (2  ed.). Duxbury.

               SIT3013   ANALYSIS  OF  FAILURE  AND  SURVIVAL
                        DATA

               Survival  distributions,  hazard  models.  Reliability  of
               systems, stochastic models. Censoring and life-tables. The
               product-limit  estimator.  Parametric  survival  models  under
               censoring. Cox proportional hazards model and other basic
               models with covariates.

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

               Medium of Instruction:
               English

               Soft Skills:
               CS1, CTPS2

               References:
               1.   Sherwin  D.J.,  &  Bossche  A.  (2012),  The  reliability,
                   availability   and   productiveness   of   systems.
                   Netherlands: Springer.
               2.   Peter J. Smith. (2002). Analysis of failure and survival
                   data. Chapman & Hall.
               3.    Tableman  M.,  &  Kim  J.S.  (2004).  Survival  analysis
                   using  S:  Analysis  of  time-to-event  data.  Chapman  &
                   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
               posterior sampling. Bayesian decision theory. Application to
               real-world problems.

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

               Medium of Instruction:
               English

               Soft Skills:
               CS3, CTPS3

               References:
                1.   Lee,  P.  M.  (1991).  Bayesian  statistics:  an
                    introduction. Oxford University Press.
                2.   Hoff,  P.  D.  (2009).  A  first  course  in  Bayesian
                    statistical methods. Springer.
                3.   Koch,  K.  (2007).  Introduction  to  Bayesian  statistics
                     nd
                    (2  ed.). Springer.
                4.   Cowles,  M.  K.  (2013).  Applied  Bayesian  statistics:
                    With R and OpenBUGS examples. Springer.


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