# Core modules financial mathematics 211 ias 211 module

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Core modules Financial mathematics 211 (IAS 211) Module content: Principles of actuarial modelling, cash-flow models, the time value of money, interest rates, discounting and accumulating, level annuities, deferred and increasing annuities, equations of value. Module credits 12.00 Service modules Faculty of Economic and Management Sciences Prerequisites IAS 111, IAS 121, WTW 114, WTW 123, WTW 124, WTW 152, WST 111, WST 121 Contact time 1 practical per week, 3 lectures per week Language of tuition Module is presented in English Department Actuarial Science Period of presentation Semester 1 Contingencies 221 (IAS 221) Module content: Fundamentals of survival models, select and ultimate life tables, Assurance and annuity functions, basic calculation of premiums and reserves, principles of pricing and reserving. Module credits 12.00 Prerequisites IAS 211 Contact time 1 practical per week, 3 lectures per week Language of tuition Module is presented in English Department Actuarial Science Period of presentation Semester 2
University of Pretoria Yearbook 2019 | | 11:24:48 18/03/2019 | Page 13 of 23 Mathematical statistics 211 (WST 211) Module content: Set theory. Probability measure functions. Random variables. Distribution functions. Probability mass functions. Density functions. Expected values. Moments. Moment generating functions. Special probability distributions: Bernoulli, binomial, hypergeometric, geometric, negative binomial, Poisson, Poisson process, discrete uniform, uniform, gamma,exponential, Weibull, Pareto, normal. Joint distributions: Multinomial, extended hypergeometric, joint continuous distributions. Marginal distributions. Independent random variables. Conditional distributions. Covariance, correlation. Conditional expected values. Transformation of random variables: Convolution formula. Order statistics. Stochastic convergence: Convergence in distribution. Central limit theorem. Practical applications. Practical statistical modelling and analysis using statistical computer packages and the interpretation of the output. Module credits 24.00 Service modules Faculty of Engineering, Built Environment and Information Technology Faculty of Economic and Management Sciences Faculty of Natural and Agricultural Sciences Prerequisites WST 111, WST 121, WTW 114 GS and WTW 124 GS Contact time 4 lectures per week, 2 practicals per week Language of tuition Module is presented in English Department Statistics Period of presentation Semester 1 Applications in data science 212 (WST 212) Module content: Introduction to database design, extracting data from databases using different software packages. Introduction to machine learning. Commonly used machine learning techniques Module credits 12.00 Prerequisites WST 111, WST 121, WTW 114 (GS), WTW 124 (GS). Contact time 2 lectures per week, 1 practical per week Language of tuition Module is presented in English Department Statistics Period of presentation Semester 1 Mathematical statistics 221 (WST 221) Module content: Stochastic convergence: Asymptotic normal distributions, convergence in probability. Statistics and sampling distributions: Chi-squared distribution. Distribution of the sample mean and sample variance for random samples