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Second Year Statistics Modules

TitleDistribution Theory
CodeSSTT111, SSTT112DepartmentMathematical Sciences
PrerequisitesNoneCo-requisitesSMTH111, SMTH112, SMTH221
AimTo introduce fundamental continuous distributions and their properties which will be used in Statistical Inference and which will form the foundation for all third year level statistics modules.
Content
  • Random variables of the continuous type; Continuous distributions – probability density function, cumulative distribution function, and moments; Special continuous distributions; Distributions of functions of random variables; Mixed distributions; Distributions of two continuous random variables; Correlation coefficients; Marginal distributions; Conditional distributions; The bivariate normal distribution; Transformations of random variables; Independent random variables; Distributions of sums of independent random variables; Random functions associated with the normal distribution; Approximations for discrete distributions; The central limit theorem; Limiting distributions; Chebychev’s inequality and convergence in probability.
Assessment40% Continuous Assessment Mark
60% Formal end of module exam (3 hours)
DP Requirement40% Continuous Assessment Mark
80% Attendance at lectures and tutorials.

TitleStatistical Inference
CodeSSTT212DepartmentMathematical Sciences
PrerequisitesSSTT111, SSTT112Co-requisitesSSTT211, SMTH221, SMTH222
AimTo introduce students to estimation, and parametric- and nonparametric hypothesis tests.
Content
  • Order statistics; Maximum likelihood, methods-of-moments, and ordinary least squares estimation methods; Properties of estimation; Point estimation of means, variances, proportions, and differences; Sampling distributions; Confidence intervals for means, variances, proportions, and differences; Sample size calculations; Distribution-free confidence intervals; Simple linear regression point- and interval estimation of regression parameters; Hypothesis tests for single parameters (mean, variance, proportion, and regression parameters) and differences (between means, variances, proportions, and regression parameters); Contingency tables – goodness-of-fit test, and test for independence; Introduction to ANOVA; Nonparametric tests – Wilcoxon, Kolmogorov-Smirnov, and Runs test; Sufficient statistics; Power of a statistical test; Best critical regions; Uniformly most powerful tests; Likelihood ratio tests.
Assessment40% Continuous Assessment Mark
60% Formal end of module exam (3 hours)
DP Requirement40% Continuous Assessment Mark
80% Attendance at lectures and tutorials.