Copyright © 2016 Mathematical Statistics STM 312 :   Advanced Mathematical Statistics A1  Contents:   Transformation of random variables, Order statistics, Families of random variables,  Sampling distributions, Limiting distributions and stochastic convergence, Point  estimation and properties of estimates, Quadratic  forms, Multivariate normal distribution.  (16 Credits)  Pre-requisites: STM221 or STM222   STM 313 :   Introductory Applied Statistics B1  Purpose:   Learners are to acquire advanced knowledge of  statistical techniques applied in deriving optimal  methods of analysing data.  Contents:   Normal  Z-score test for one and two independent  populations . Student’s t-test for one and two  independent populations. Mann-Whitney U-test.   Paired samples t-test and Wilcoxon’s Signed rank  test for  two dependent populations. One-way fixed  effects ANOVA, Kruskal-Wallis test and Two-way  fixed effects ANOVA for tests concerning more than two independent populations.  Least significant  difference and Honestly significant difference-  Tukey, Scheffe for Multiple comparison procedures.  Chi-square goodness of fit test and Chi-square test for independence for testing the  association between categorical variables.  (16 Credits)  Pre-requisites: STM221 or STM222   STM 322 :   Advanced Mathematical Statistics A2  Purpose:   Learners are to acquire an introductory knowledge of statistical software packages  and develop skills in computerised statistical data analysis.  Contents :   Theory and Applications of interval estimation. Statistical hypothesis testing.  Simple  and composite hypotheses.  Uniformly most powerful tests and likelihood ratio tests.   Analysis of Variance.  The general linear model.  Chi-squared tests and tests of  independence.  Sufficiency.  The Rao- Cramer lower bound.  (16 Credits)  Pre-requisites: STM312  STM 323 :   Introductory Applied Statistics B2  Purpose:   Learners are to acquire an introductory knowledge of statistical software packages  and develop skills in computerised statistical data analysis.  Contents :   Correlation Analysis: Pearson’s coefficient of simple correlation. Spearman’s  coefficient of simple correlation.  Partial correlation.  Simple Linear Regression:  Simple linear regression   parameter estimation and interpretation. Tests for  significance of a regression. Relationship with correlation analysis. Response  prediction.  Multiple Linear Regression Analysis:  Parameter estimation and  interpretation.  Variable selection procedures. Pearson’s coefficient of multiple  determination. Adjusted coefficient of determination. Multicollinearity.   Handling  Problem Data:  Missingness.  Outlying values.  Violation of statistical assumptions.   Diagnostic and remedial measures.  (16 Credits)  Pre-requisites: STM313    Statistics show that of those who contract the habit of eating, very few survive.   Learners are to acquire an advanced knowledge of the statistical techniques applied in the derivation of optimal methods for analysing data.   THIRD YEAR COURSES