Module Descriptors

Computing

CS102: Computer Science This module lays a broad foundation in Computer Science for students in the College of Science. It compliments the physical, life and mathematical sciences by providing the core principles of computing need for a degree in science, with an emphasis on programming. It is also the gateway to a degree in Computer Science.
CS103: Computer Science This module provides a foundation in the core principles of functional computing programming.
CS204: Computer Science ... incomplete ...
CS209: Algorithms and Scientific Computing This course covers algorithm design, analysis and implementation. The programming language used is PYTHON.
CS211: Programming and Operating Systems. This course introduces operating systems, the most fundamental piece of software running on any computer.
CS319: Scientific Computing This module introduces the fundamental principles of scientific computing, object oriented programming, and the development of mathematical software. Key ideas in object oriented programming, such as encapsulation, polymorphism and inheritance, and presented in the context of solving problems that arise in mathematical and/or statistical modelling.
CS3304: Mathematical and Logical Aspects of Computing This module introduces the fundamental concepts of propositional and predicate logic. Topics covered include the precise mathematical formulation of logical statements; the analysis of such statements to establish equivalence and consistency; and an introduction to mathematical techniques to check the validity of arguments in propositional and predicate logic.
CS402/MA492: Cryptography This course develops basic concepts in private and public key cryptosystems, explores some of the associated algorithmic number theory, and introduces more advanced topics such as the use of elliptic curves in cryptography.
CS423: Neural Networks An introductory course in Neural Networks. Topics include learning algorithms, memory, the Rosenblatt perceptron, back-propagation multilayer perceptrons, and the Hopfield network.
CS424: Object Oriented Programming/Internet Programming This course introduces computer science students to object orient programming techniques and to software architecture used for internet programming.
CS428: Advanced Operating Systems This course introduces the basics of parallel computing. Topics covered include parallel computing platforms and networks; parallel algorithm design and parallel programming in both homogeneous and heterogeneous systems.
MA160/MA190: CS Algebra ... incomplete ...
MA410: Artificial Intelligence The course covers topics in the modern Artificial Intelligence, including: optimized tree searching, game theory, propositional and predicate logic, reasoning under uncertainty, utility, and the Prolog language.
MM245: Numerical Analysis I This course teaches the basics of numerical analysis, with associated laboratories using MATLAB. Topics covered include: approximations & errors, propagation of errors, finding roots of a function, numerical interpolation, numerical integration, numerical methods for linear systems of equations, and numerical methods for simple differential equations
MM246: Numerical Analysis II This course builds on Numerical Analysis I. Topics covered include: Newton cotes formulae and error analysis, categorisation of direct and iterative numerical methods, Gauss Seidel iterative scheme and its convergence, eigenvalues and eigenvectors, Gerschgorin circle theoerm, power method and its varieties, Euler's method, Improved Euler's method, Modified (mid-point) Euler's method, fourth order Runge-Kutta method, iterative solution of algebraic equations and convergence analysis.

Mathematics

MA102: Anailis and Ailgeabar ... incomplete ...
MA111: Mathematics of Finance I ... incomplete ...
MA1222: Cultures of Mathematics ... incomplete ...
MA131: Mathematical Skills ... incomplete ...
MA133: Mathematics (Arts) ... incomplete ...
MA170: Introduction to programming for biologists This module provides biology you with foundation programming skills in Perl and enables them to perform core bioinformatic tasks. It will also introduce them to the scope for further learning and more advanced applications, and allow them to appreciate that computer-based tools are fundamental to modern biology and medicine.
MA180: Mathematics Mathematics MA180 is an introduction to university mathematics aimed at students studying the mathematical and physical sciences. Students should have achieved at least an OA2 or HC3 level in their Leaving Certificate. Around 66% of students will have studied higher level mathematics at Leaving Certificate. The module is a prerequisite for the Mathematics BSc and is a popular option for a wide range of degree programmes in the mathematical and physical sciences.
MA190: Mathematics
MA199: Statistics & Probability & Maths Of Finance PAPER I: Paper I is intended as a first course in probability taken by students studying a degree in which mathematics is to be the main subject throughout that degree as it provides a good foundation to higher level probability and statistics courses. PAPER II: Paper II material is intended as a first course in statistics for students studying a degree in which mathematics is to be the main subject throughout that degree as it provides a good foundation to higher level probability and statistics modules. The material in paper I is a prerequisite for this material. PAPER III: Simple interest and simple discount, bank discount and negotiable instruments, compound interest and discount, equivalent dates and rates, exponential and logarithm functions, annuities (all types), perpetuity, capitalization, depreciation, loans (amortization and sinking funds).
MA221: History of Maths I ... incomplete ...
MA283: Linear Algebra This course covers the theory and practice of Linear Algebra.
MA284: Discrete Mathematics This course covers topics in combinatorics, graph theory, and their applications. Section titles are as follows. Addition and multiplication principles; Permutations and combinations; Ordered and unordered selections with repetition; Inclusion and Exclusion; Graph isomorphism, subgraphs, connectedness; Traveling around a graph; Vertex coloring; Planarity; Trees.
MA286: Analysis I Introduction to functions of several variables and vector valued functions. Topics include partial derivatives, local extrema, curvature, parametric curves, double integrals, Green's Theorem .
MA287: Analysis II This module introduces the theory of functions of a complex variable, statring with an introduction to complex numbers and ending with applications of the Residue Theorem and conformal transformations.
MA310: Actuarial Mathematics This module introduces students to the basic theory of actuarial mathematics. Students who successfully complete the module can earn an exemption on the Institute of Actuaries CT1 exam. The module covers actuarial notation, project appraisal, investments, forward contracts, interest rate term structures.
MA3101: Euclidean and Non-Euclidean Geometry ... incomplete ...
MA311: Annuities and Life Assurance This course is the learner's first course in actuarial science. Topics covered include: life table (select and ultimate); probability of survival; payments on survival e.g. annuities, pure endowments; payments on death e.g. life assurance; accumulation with survivorship benefit; net and office premiums; future life time
MA341: Metric Spaces This module introduces the theory of metric spaces. The real line with its natural notion of distance is a metric space, from which the metric space definition and theory readily evolves. Familiar concepts such as convergence and continuity are explored in this new broader context while new concepts and properties, such as closed sets and compactness, illuminate key basic facts about functions.
MA342: Topology An introduction to the theory and application of topology.
MA343: Groups I Introduction to Group Theory. Topics covered include the group axioms, symmetries, permutations, cyclic groups, dihedral groups, small groups of matrices, homomorphisms, normal subgroups, Isomorphism Theorems, automorphism groups, free groups, relators and presentations.
MA344: Groups II The course covers monoids and groups and their actions. Topics covered include finite state machines, orbits and stabilizers, applications in combinatorics (e.g. vertex colorings), Sylow theory, finite simple groups.
MA378: Numerical Analysis II Polynomial interpolation and its applications in numerical integration, numerical differentiation, splines, and finite element methods for ODEs.
MA385: Numerical Analysis I This module is a first course on the mathematical analysis of numerical methods for solving important computational problems. Topics covered include: Solving nonlinear equations; Technques for computing solutions to initial value problems; Matrix factorisation methods for solving linear systems; The estimation and applications of eigenvalues.
MA416: Rings An introduction to ring theory, covering topics like PIDs, Polynomial rings, and Euclidean rings.
MA418: Differential Equations with Financial Derivatives This course introduces the theory of Stochastic Differential Equations. Topics covered include Gaussian Processes, Brownian Motion, Martingales, Stochastic Integrals, Ito's Lemma's, Stochastic Differential Equations, Call and Put Options and the Black-Scholes model.
MA419: Statistics This module is an introductory statistics course for students in areas such as Environmental Science, Microbiology, Analytical Biochemistry and Chemistry. Emphasis is on basic probability and a battery of applied statistical techniques for analysing qualitative and quantitative data from experiments and observational studies.
MA430: Mathematics Project In this module, the student works on a Mathematics problem under the supervision of an academic at the School of Mathematics, Statistics and Applied Mathematics. The student is required to produce a mid-term project report, a final project report, and to deliver an oral presentation on the project to members of the School.
MA435: Undergraduate Ambassador Module in Mathematics This is a service learning module in Mathematics. Each student will be placed with a mathematics teacher in a local post-primary school for approximately three hours per week, for 9 to 10 weeks. During this period the student engages in tasks assigned and supervised by the teacher, including - classroom observation and assistance; - teaching assistance involving interaction with 2nd level students; - completion of a project; - coordination and facilitation of extra-curricular activities.
MA437: Introduction to Mathematical Research Topics I ... incomplete ...
MA438: Introduction to Mathematical Research Topics II ... incomplete ...
MA482: Functional Analysis This course introduces the theory of Linear Functional Analysis. Topics include Banach Spaces, Bounded Linear Operators, Dual Spaces, Hilbert Spaces, Orthogonal Complements and Direct Sums, Representation of Functionals on Hilbert Spaces and the Hilbert-Adjoint Operator.
MA490: Measure Theory A "measure" on a set is a systematic way to assign a number to each suitable subset of that set, intuitively interpreted as its size. Measure is a generalization of the concepts of length, area, and volume. An important example is Lebesgue measure, which assigns the conventional length, area and volume of Euclidean geometry to suitable subsets of n-dimensional space. Measure Theory is the basis for Integration and it is the foundation for an understanding of Probability Theory.
MA491: Field Theory This is an introduction to the theory of Field Extensions, their Galois groups and the application of finite fields to constructing BCH codes.
MA495: Actuarial Mathematics: Life Contingencies II This course introduces some material on Life Contingencies. Topics include Multiple Lives (including Joint Life and the Last Survivor Status), the Z Method, Contingent Probabilities and Assurances, Multiple Decrement Tables, Random Vectors and Distributions.

Business

MA109: Statistics for Business This module follows on from MA119 Mathematics for Business and continues to equip students with mathematical and statistical skills required in Business, Economics, Finance and Marketing. The statistics content in the module suffices as a first course in descriptive statistics, probability theory and sampling theory, and serves to equip students with the tools they need to progress to inferental statistics in MA217 Statistical Methods for Business.
MA119: Mathematics for Business
MA208: Quantitative Techniques for Business This is a core module of the second year of Business Information System (BIS) Bachelor studies. This course aims at creating a basic understanding of elementary mathematical concepts that are of common use in business, as well as to establish familiarity with some simple tools useful for dealing with business quantitatively.
MA217: Statistical Methods for Business This module demontrates methods in statistical inference with applications in Business, Finance, Marketing and Ecomomics. This is a first course in statistical inference covering sampling distributions, contruction of confidence intervals and hypothesis testing, and communication of results of analysis applied to a range of business problems. Students must have completed an introductory course in descriptive statistics and probability similar to the content of MA109 Statistics for Business.
MA218: Advanced Statistical Methods for Business This module demontsrates further applications in inferential statistics with applications in Economics, Business, Marketing and Finance. Students are required to have completed an introductory course in Descriptive Statistics and Probability equivalent to MA109 Statistics for Business and an introductory course in Inferential Statistics, equivalent to MA217 Statistical Methods for Business. Lectures will be used to present the ideas of statistical theory and practice, these will include demonstrations of real-life statistical analyses based on business oriented problems. Students will be required to apply the methodology to example datasets using suitable statistical software, SPSS. The tutorials and practical sessions will give support for this aspect of the course.

Mathematical Studies

MA135: Mathematics (Arts) ... incomplete ...
MA160: Mathematics
MA161: Mathematical Studies Mathematical Studies MA161 is an introduction to university mathematics aimed at students studying the physical and life sciences. The majority of MA161 students will have studied ordinary level mathematics at Leaving Certificate, though some will have studied the subject at higher level. Although students are unable to proceed from this module to a Mathematics BSc, the module does lead on to a range of second and third year Mathematical Studies modules relevant to the physical and life sciences. (By taking a total of 60 ECTS of appropriate Mathematical Studies modules during their undergraduate studies, students can satisfy the Teaching Council's subject requirements for mathematics teachers while majoring in another Science subject.)
MA203: Linear Algebra An introduction to the theory and application of linear algebra.
MA204: Discrete Mathematics This course deals with elementary enumeration, permutations, combinations, and graphs including eulerian and hamiltonian graphs.
MA211: Calculus I This is a continuation of first year Calculus, dealing with more advanced topics. Further techniques of integration, reduction formulas, volumes of revolution. Introduction to Hyperbolic functions and their inverses. Series and convergence. Improper Integrals. Some differential equations.
MA212: Calculus II An introduction to the calculus of functions of two variables, and vector valued functions. The topics include: Vectors; Multivariate Calculus; Optimization of elementary multivariate functions; Integration of elementary multivariate functions over polygons.
MA301: Advanced Calculus This calculus course builds on earlier basic calculus knowledge. Topics covered include: convergence of sequences & series, Taylor's & the Maclaurin series, multiple integrals using Cartesian, polar and elliptical coordinates, Fourier series, computation of line integrals directly and by using Green's theorem.
MA302: Complex Variables This course introduces complex variable theory. Topics covered include: Cauchy-Riemann equations, Laplace's equation, complex numbers to the power of complex numbers, Integral evaluation in the complex plane, Cauchy's integral theorem, Cauchy's integral formula and Cauchy's integral formulae for derivatives, residues and the residue theorem.
MA313: Linear Algebra An advanced course in the theory and application of linear algebra, including the theory of vector spaces, linear independence, dimension and linear mappings.
MA321: Computer Packages ... incomplete ...
MA334: Geometry This module is an introduction to the ideas and methods of classical and modern geometry.
MA335: Algebraic Structures An introduction to the theory and application of modern abstract algebra.

Engineering

MA140: Engineering Calculus Syllabus Outline: Limits, continuity, intermediate value theorem, differentiation, logarithms. These tools are used to tackle verbally stated engineering problems involving rates of change and maxima and minima. Basic properties of integrals, Fundamental Theorem of Calculus, method of substitution, integration by parts, partial fractions and the logarithm rule. These tools are used to solve verbally stated engineering problems involving integration techniques.
MA2101: Mathematics and Applied Mathematics I This module covers topics in both Mathematics and Applied Mathematics for engineering students. The material presented includes: calculus of several variables, multiple integration and integral theorems, coordinate systems, force systems, rigid body motion, Fourier series, and Laplace transforms.
MA2102: Mathematics and Applied Mathematics II This module considers topics in both Mathematics and Applied Mathematics for engineering students. The material covered includes linear algebra, sequences and series, complex analysis, dimensional analysis, and partial differential equations.
MM140: Mathematical Methods for Engineers
MP120: Engineering Mechanics
ST500: Advanced Engineering Statistics This module will provide a second level coverage of statistics with an emphasis on topics of use to engineers and practical hands-on experience of applied statistics using statistical software.

Bioinformatics

MA215: Mathematical Molecular Biology This course covers mathematical and algorithmic methods applied to problems in molecular biology, including genome sequence assembly, DNA and amino acid sequence alignment, phylogenetics and models of RNA secondary structure.
MA216: Mathematical Molecular Biology II This module is intended to give students an understanding and knowledge of the application of mathematical or algorithmic methods to defined problems in molecular biology. The focus is primarily on problems involving mutation discovery and evolutionary inference to predict mutation frequencies in a population as they change over time, and how to detect mutations of interest.
MA324: Introduction to Bioinformatics This module provides biology students with foundation knowledge of bioinformatics and enables them to perform basic bioinformatic tasks. It will also introduce them to the scope for further learning and more advanced applications, and allow them to appreciate how bioinformatic tools are fundamental to modern medicine.
MA461: Probabilistic models for molecular biology This course covers applications of probabilistic models and related techniques in genomics and systems biology. Beginning with a review of stochastic processes, the course will consider the use of Hidden Markov models (HMMs) to predict genes and identify genomic regions with shared epigenetic characteristics; the use of continuous-time Markov processes to model molecular evolution; applications of Gibbs sampling to infer haplotypes from genotype data among other models and applications.
MA570: Introduction to Genomics This module will give students skills associated with high-throughput processing, investigation and interpreting the output of genomics data using bioinformatic tools.

Applied Mathematics

MP180: Applied Mathematics This is an introductory course in Applied Mathematics. The material presented assumes no prior knowledge of applied mathematics or honours second level mathematics. The course is of value to any student interested in the direct use of mathematics in real-world applications. This course also prepares the learner for more advanced topics in later years such as advanced mechanics and mathematical methods, mathematical modelling, non-linear systems, elasticity, quantum mechanics, electromagnetism, fluid mechanics, cosmology and general relativity.
MP191: Mathematical Methods I The module is designed as an introductory course to the theory and applications of linear difference and ordinary differential equations. The module includes many examples of how these types of equations are used to describe real applications, especially economics applications. No prior knowledge of difference or differential equations is assumed.
MP211: Modelling, Analysis and Simulation This course is designed to introduce the concepts, analysis methods and economic applications of dynamical systems. A project describing different models will be presented at the end of the course.
MP231: Mathematical Methods I This course covers mathematical methods (principally from Calculus) that are important in applications. Included are differentiation and integration of functions of multiple variables and associated applications such as optimization (Lagrange Multipliers), critical points, Fourier series, and area/volume calculations.
MP232: Mathematical Methods II This is a mathematical methods course that considers the following topics: Laplace transforms, vector calculus, multiple integration and integral theorems
MP236: Mechanics I This is a mechanics course for students who have already been exposed to an elementary mechanics course. Topics covered include dimensional analysis, variational calculus, Lagrangian mechanics and rigid body motion.
MP237: Mechanics II This course consists principally of an introduction to the theory and applications of partial differential equations. Topics covered include the heat equation, the wave equation, Laplace's equation, and a brief introduction to the special theory of relativity.
MP305: Modelling I This course introduces the student to modelling techniques for four different real-world problems. The problems cover the topics network-flow optimisation, activity networks, traffic flow and game theory.
MP307: Modelling II This course introduces the student to modelling techniques for three different real-world problem areas. The problems cover the topics queueing theory, population dynamics and control theory.
MP345: Mathematical Methods I This course introduces some advanced methods of mathematical physics for solving ordinary differential equations, and presents some applications of complex analysis.
MP346: Mathematical Methods II This is a mathematical methods course, and amongst the topics considered are the heat equation, Laplace's equation, Sturm-Liouville theory, the Fourier transform, and the numerical solution of partial differential equations using finite difference techniques.
MP356: Quantum Mechanics I (This course will be run every other year.) This is an introductory course to 1- dimensional quantum mechanics. The course covers topics such as the Schrodinger equation and wave functions, infinite and finite square well potentials, the harmonic oscillator, wave packets, vector spaces and the uncertainty principle.
MP357: Quantum Mechanics II (This course will be run every other year.) This is a continuation of MP356 and covers topics such as the 2-d and 3-d Schrodinger equation, spherically symmetric potentials, spherical harmonic functions, the hydrogen atom, angular momentum eigenstates, spin, spin-statistics, addition of angular momentum, rotations of a spinor, measurement in quantum mechanics, hidden variables and the Einstein- Podolsky-Rosen paradox, Bell's theorem.
MP365: Fluid Mechanics (This course will be run every other year.) This course consists of an introduction to the theory of fluid mechanics. Topics covered include: a review of vector calculus, ideal fluids, irrotational flow, Laplace's equation and some potential theory, elementary viscous flow with examples, the stress tensor, Cauchy's equation of motion, the Navier-Stokes equations, very viscous flow, including thin film and lubrication theory.
MP366: Electromagnetism (This course will be run every other year.) This course introduces the theory of electromagnetism. Topics covered include electrostatics, the electrostatics of materials, magnetostatics, the magnetostatics of materials, and a brief introduction to Maxwell's laws.
MP403: Cosmology and General Relativity In the study of cosmology where gravitation is the dominant force over the large scales considered, general relativity is the basic component. This course introduces general relativity. Topics covered include geometry, geodesics, black holes, different model universes and cosmogony.
MP410: Nonlinear Elasticity (This course will be run every other year.) Description: This course is concerned with continuum mechanics applied to the behaviour of elastic solids. Topics covered include Tensor algebra, Kinematics of continuum deformation and motion, Balance laws and equations of motion, Constitutive equations for soft elastic materials.
MP491: Nonlinear Systems This course is an introductuion to the analysis of systems of nonlinear Ordinary Differential Equations (ODEs) and Maps.
MP494: Partial Differential Equations (This course will run every other year.) This course introduces the theory of partial differential equations (PDEs).Topics covered include first order PDEs, linear second order PDEs in two variables, maximum principles and well-posedness of problems, separable variable and similarity solutions.
MP553: Advanced Applied Mathematics for Engineers 1 This course introduces some advanced methods of applied mathematics for solving ordinary differential equations and using complex analysis, with a view to engineering applications. The topics covered include: 1. Linear Second Order Ordinary Differential Equations; 2. Power Series Solutions; 3. The Frobenius Method; 4. Special Equations; 5. Complex Analysis; 6. Application to vibrations, waves, flows.
MP554: Advanced Applied Mathematics for Engineers 2 This is a follow-up on the course Advanced Applied Mathematics for Engineers 1 (new code). Topics covered include: (i) The 1-dimensional heat equation. Introduction to Initial Value Boundary Value Problems. Solution for various boundary conditions and initial conditions. (ii) Sturm-Liouville Systems. General properties and application to simple systems. (iii) The 2-dimensional Laplace equation. Solution for various boundary conditions on a rectangular or rotationally symmetric region; (iv) The Fourier Transform. Properties, the inverse transform. Application to solving the 1- dimensional heat equation on an infinite region. (v) Finite difference methods. Application to numerically solving the 1-dimensional heat equation. Stability of numerical method

Statistics

ST1100: Engineering Statistics ... incomplete ...
ST112: Probability The module is intended as a first course in probability taken by students studying a degree in which mathematics is to be the main subject throughout that degree as it provides a good foundation to higher level probability and statistics courses.
ST113: Statistics The module is intended as a first course in statistics for students studying a degree in which mathematics is to be the main subject throughout that degree as it provides a good foundation to higher level probability and statistics modules. ST112 or its equivalent is a prerequisite for this module.
ST2101: Introduction to Probability and Statistics ... incomplete ...
ST235: Probability This is an introductory course to probability theory. Topics include: algebra of events, concepts of conditional probability and independence of events; random variables (rv); discrete and continuous propability distributions; expectation, variance and functions of rv-s; probability and moment generating functions; basic probability inequalities.
ST236: Statistical Inference An introduction to the ideas of statistical inference from a mathematical perspective. Topics covered include: populations and samples, properties of estimators, likelihood functions, principles and methods of point estimation, interval estimates, hypothesis testing and construction of tests.
ST237: Introduction to Statistical Data and Probability This course discusses the nature of statistical data and the use of probability to describe random phenomena. Topics covered include: data sources, data presentation, numerical and graphical summaries, basic ideas of probability, conditional probability and indpendence, random variables, standard discrete distributions, mean and variance, joint distributions, and an introduction to the normal distribution.
ST238: Introduction to Statistical Inference This module is an introduction to the ideas and commoly used techniques in analysing data from experiments and observational studies. Participants learn the role of probability in statistical inference, review the ideas in sampling distributions, learn concepts of interval estimation and hypothesis tests, learn standard one and two-sample procedures for quantitative data, learn basic enumerative data analysis, and simple correlation and linear regression
ST311: Applied Statistics I An introduction to methods and applications in applied statistical inference. This module is offered as an optional module, building on the statistical inferential methods demonstrated in pre-requisite module MA238/ST238 or MA228 or similar modules. Various non-parametric hypothesis tests are demonstrated and a comparison of suitability of applying non-parametric and parametric methods is discussed. The module also builds on regression modelling, where topics covered include model estimation, model checking and inference for simple linear regression and multiple linear regression models, and procedures in variable selection. Models discussed are applicable for a single quantitative response with quantitative and/or qualitative predictors.
ST312: Applied Statistics II Methods and applications in applied statistical inference. This module discusses factors for consideration in experiment design and demonstrates methods in the analysis of data emerging from desiged experiments. Topics covered include confounding, blocking, a completely randomized design and a randomized block design, two-way ANOVA. The module also demonstrates regression modelling for a qualitative response, i.e. methods in logistic regression and generalized linear models, and various techniques in analysis of a multivariate response, including topics from, principal components analysis, cluster analysis, time series analysis etc. This module is built on ST311.
ST313: Applied Regression Models An introduction to the theory and application of regression models. Topics covered include the simple linear model, least-squares estimation, multiple linear regression, inference, model checking, model choice and variable selection, and the use of Minitab for practical applications. This module is built on the statistical inference methods demonstrated in pre-requisite module ST236.
ST314: Introduction to Biostatistics This course will introduce students to statistical concepts and thinking by providing a practical introduction to data analysis. The importance and practical usefulness of statistics in biomedical and clinical environments will be demonstrated through a large array of case studies. Students attending this course will be encouraged and equipped to apply simple statistical techniques to design, analyse and interpret studies in a wide range of disciplines.
ST411: Mathematical Statistics: Point Estimation NOT RUNNING IN ACADEMIC YEAR 2013-2014. This module provides a mathematical approach to data reduction and estimation in statistics. Primary focus is on the development of optimal theory of estimation in parametric models using various criteria.
ST412: Stochastic Processes RUNNING IN ACADEMIC YEAR 2016-2017. The goal of the course is to introduce the main ideas and methods of stochastic processes with the focus on Markov chains (processes with discrete time index and finite state space). Branching processes and Poisson process (continuous time and discrete state space) will also be included in the study.
ST413: Statistical Modelling An advanced course on statistical modelling, building on the regression modelling introduced in MA322/ST313, covering the theory and application of generalized linear models and their fitting in R
ST414: Statistical Theory - Hypothesis Testing NOT RUNNING IN ACADEMIC YEAR 2013-2014. An advanced course on aspects of statistical theory with an emphasis on the principles and practice of hypothesis testing. Topics covered include hypotheses, test construction and critical regions, size and power, most powerful tests, Neyman-Pearson approach, likelihood methods, likelihood based tests, and an introduction to asymptotic results.
ST415: Probability Theory and Applications This module develops probability theory that is useful in a myriad of applications. The theory is implemented in the development of statistical theory and methods, and a variety of applications will be given in IT and Communications Systems, and in other areas. The module is quite advanced and requires knowledge of probability to the level of at least ST235 or equivalent, and preferably also some mathematical statistics.
ST416: Time Series Analysis MODULE AVAILABILITY SUBJECT TO SUFFICIENT ENROLLMENT NUMBERS This module mixes statistical theory and practice to develop and implement models for the analysis of time series data. The module is a relatively advanced course that requires knowledge of probability and mathematical and applied statistics such as that in the modules ST235, ST236 and ST313.
ST417: Introduction to Bayesian Modelling An introductory course to Bayesian statistical modelling and analysis. Covers basic theory and methods of Bayesian model development and focuses on inference which is based on simulations (computations done in R). A prerequisite is a calculus based course in probability (at the level of MA235, for example). Prior experience studying statistics or regression analysis is helpful but not necessary.