Page 173 - FINAL_HANDBOOK_20242025
P. 173

Faculty of Science Handbook, Academic Session  2024/2025




               single  population;  difference   Assessment:
               between two means, difference   Continuous Assessment: 50%
               between  two  proportions  and   Final Examination: 50%
               ratio  of  variances.  Chi-square
               goodness-of-fit   tests   and
               contingency tables.            SIT2008
                                              FURTHER MATHEMATICAL
               Power of a statistical test. Best   STATISTICS
               critical  region.  Likelihood  ratio
               test.  Chebyshev's  inequality.   The   exponential   family;
               Convergence in probability and   sufficient,   complete   and
               distribution.   Asymptotic     ancillary  statistics;  minimum
               distribution   of   maximum    variance  unbiased  estimators;
               likelihood   estimator.   Rao-  Bayesian  estimation;  Delta
               Cramer's inequality.           method    for   asymptotic
                                              approximation;  distributions  of
               Assessment:                    certain  quadratic  forms-one
               Continuous Assessment: 40%     and  two  factors  analysis  of
               Final Examination: 60%         variance;  probability  measure
                                              space;  law  of  large  numbers;
                                              Borel-Cantelli lemma.
               SIT2007
               FOUNDATIONS OF DATA            Assessment:
               SCIENCE                        Continuous Assessment: 40%
                                              Final Examination: 60%
               Introduction  to  data  science;
               Differences       between
               experimental          and      SIT2009
               observational        data;     REGRESSION ANALYSIS
               Characteristics of big data sets;
               Sources of biases in data sets;   Simple   linear   regression:
               Introduction  to  industry-level,   Estimation, hypothesis testing,
               open  source  computing  tools   analysis   of   variance,
               such as R; Data management;    confidence       intervals,
               Graphical      visualisation   correlation,  residuals  analysis,
               including spatial data; Analysis   prediction.     Model
               and  interpretation  of  real  data   inadequacies,   diagnostics,
               sets  with  varying  degrees  of   heterogeneity   of   variance,
               complexity  using  appropriate   nonlinearity,   distributional
               statistical methods.           assumption,       outliers,
                                              transformation.   Selected
                                              topics  from  matrix  theory  and
                                              multivariate normal distribution.





                                          173
   168   169   170   171   172   173   174   175   176   177   178