You'll study the basic concepts and standard methods of mathematical notation and proof, polynomial equations and inequalities, sequences and series, functions, limits and continuity, differentiation and integration.

The fundamental concepts of calculus (differentiation and integration) presented in Applications of Calculus will be examined in more detail, extended to a larger class of functions by means of more sophisticated methods, including an introduction to complex numbers and variables. These will all be demonstrated in application to practical problems including solving basic first and second-order differential equations.  

This module will introduce you to vectors and matrices, along with the idea of mathematical modelling through their application to real-world problems.

Some basic ideas and techniques of statistics will be presented while introducing some essential study skills, allowing you to develop and practice personal and technical skills, e.g. self-study, teamwork, analysing data, writing reports and making presentations.

The module will provide you with a balanced introduction to economics which will be based on a programme of systematic directed reading, supplemented by experiments and exercises undertaken in tutorials. 

The module uses the innovative COREecon resources, which provides a complete introduction to economics and the economy. COREecon teaches about the economy and economics by starting from a question or a problem about the economy - why the advent of capitalism is associated with a sharp increase in average living standards, for example - and then teach the tools of economics that contribute to an answer. This innovative approach ensures that students understand how the tools of economics can help us understand the modern economy. 

The second half of the module is the study of how analytical thinking, scientific method and associated tools can be used to help decision making. This Business Analysis element of the module will provide an overview of where methods and tools are widely used across a large range of industries including the manufacturing, retail, healthcare, financial services, travel, and electronics industries, as well as in local and national government. 

Examples of where Business Analysis is put into practice are: 

• the management of new building projects
• the design of efficient transport systems and plant layouts
• personnel scheduling
• allocation of resources and financial modelling and forecasting

This area of expertise can help to reduce costs, increase revenues, improve customer service, increase efficiency and can even save lives. 

This module will introduce you to the basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors. You'll study various standard methods for solving ordinary differential equations and understand their relevance.

This module will present basic ideas, techniques and results for calculus of two and three variables, along with differentiation and integration over curves, surfaces and volumes of both scalar and vector fields.

This module will present the basic concepts of probability theory and statistical inference to provide you with the tools to appropriately analyse a given data set and effectively communicate the results of such analysis.

This module will introduce you to the R computing environment. It'll enable you to use R to import data and perform statistical tests, allow you to understand the concept of an algorithm and what makes a good algorithm and will equip you for implementing simple algorithms in R.

This module is one of the two undergraduate Business Analysis & Technology modules before the Honours year that apply various approaches to operations management problems. Following on from the fundamentals in the first year module, this module introduces you to the subject of operations management in detail and provides opportunity for you to apply some of the basic decision analysis techniques, including simulation, in this context.

This module forms a bridge between the first year module and more advanced modules in Enterprise Resource Planning, Business Process Outsourcing, the role of ICT in business environment, etc.

The module will seek to combine conceptual and technical skills, and it will provide the basis for a series of modules in third and Honours years, especially in areas of Business Process Integration with ERP, organisational innovation and E-commerce.

In this module we'll introduce you to analytical methods for solving ordinary and partial differential equations, so you’ll develop an understanding along with technical skills in this area.

This module will:

• review the concepts of probability distributions and how to work with these
• present approaches to parameter estimation, focusing on maximum likelihood estimation, bootstrap estimation, and properties of estimators
• present hypothesis testing procedures, including classical likelihood ratio tests and computer-based methods for testing parameter values, and goodness-of-fit tests.
• introduce and provide understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures
• present use of R functions for regression and interpretation of R output

The first part of this module will introduce and build experience in two problem structuring methods, SODA and Soft Systems Methodology. The second part will establish an overall understanding of how supply chains work as well as appropriate modelling approaches to address various operational challenges. The third part of the module will introduce basic mathematical optimisation modelling and present how it can be used to tackle problems in different business systems, including applications in supply chains.

The fourth and final part of the module will introduce you to the ideas of Multi-criteria Decision Analysis to make you aware of the importance of carefully defining objectives when intervening in business systems. Overall, the module will equip you with the qualitative and quantitative analytic skills and techniques in order to make action recommendations for performance improvements in complex business systems.

In this module, you will develop a comprehensive picture about knowledge and innovation. It goes to the very basis of what constitutes knowledge and knowledge work, and based on this, develops the notion of creativity, as creation of new knowledge, and subsequently conceptualises innovation as new value created from the new knowledge.

This module will introduce functions of a complex variable, define concepts such as continuity, differentiability, analyticity, line integration, singular points, etc. You will examine some important properties of such functions and consider some applications of them, e.g. conformal mappings and the evaluation of real integrals using the Residue Theorem. You will also be introduced to Fourier and Laplace transform methods for solving linear ordinary differential equations and convolution type integral equations.

In this module we'll introduce basic algebraic structures, with particular emphasis on those pertaining to finite dimensional linear spaces and deepen your understanding of linear mappings. We'll also provide an introduction to inner product spaces and bilinear forms.

This module will motivate the need for numerical algorithms to approximate the solution of problems that can’t be solved with pen and paper. You will develop your skills in performing detailed analysis of the performance of numerical methods and will continue to develop your skills in the implementation of numerical algorithms using R.

In this module you will be introduced to the basic concepts of random phenomena evolving in time, from two complementary points of view: probabilistic modelling and data-driven analysis.

Presentation of underlying ideas of simple stochastic processes, time series models, and the associated probability theory and statistical techniques will be covered. You will also learn about the applications of the methods to financial and economic systems, including modelling, data analysis, and forecasting.

This module provides you with experience of the skills required to undertake project work, and to communicate the findings in written and oral form using a variety of sources, such as books, journals and the internet. You will undertake an individual research project, researching a mathematical or statistical topic and writing a short report on it.

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You will write a dissertation on an aspect of business analysis.

You will be provided with a range of applied statistical techniques that can be used in professional life. This module provides you with the fundamental principles of statistical modelling through experimental design and multivariate analysis.

In this module you'll be introduced to a range of modern statistical methods and practices used in industry, commerce and research, and will develop skills in your application and presentation.

This module will cover the fundamental statistical methods necessary for the application of classical statistical methods to data collected for health care research. There will be an emphasis on the use of real data and the interpretation of statistical analyses in the context of the research hypothesis under investigation.

Topics covered will include:

• survival analysis
• analysing categorical data using hypothesis tests
• experimental Design and sampling
• clinical measurement

In this module, you’ll get an introduction to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives. The module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes).  In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced. 

The first half of the module introduces general modeling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.

In this module you'll get an introduction to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives. This module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced.

The first half of the module introduces general modelling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.

This module will present the main results in Functional Analysis., You will also be introduced to linear operators on Banach and Hilbert spaces and study applications to integral and differential equations.

In this module you'll be introduced to the theory of Newtonian fluids and its application to flow problems and the dynamics of waves on water and in other contexts.

In this module you'll be presented with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.

In this module you'll learn the application of mathematical models to a variety of problems in biology, medicine, and ecology. The module will show:

• the application of ordinary differential equations to simple biological and medical problems
• the use of mathematical modelling in biochemical reactions
• the application of partial differential equations in describing spatial processes such as cancer growth and pattern formation in embryonic development
• the use of delay-differential equations in physiological processes

The marine population modelling element will introduce the use of difference models to represent population processes through applications to fisheries, and the use of coupled ODE system to represent ecosystems. Practical work will include example class case studies that will explore a real-world application of an ecosystem model.

This module will demonstrate the central role network theory plays in mathematical modelling. It'll also show the intimate connection between linear algebra and graph theory and how to use this connection to develop a sound theoretical understanding of network theory. Finally, it'll apply this theory as a tool for revealing structure in networks.

An important aspect of this module is the experiential learning element, where you'll work in teams on management science projects, directly for external clients.

The clients will introduce their problems, provide information during the project, and listen to your recommended solutions. These client projects will be chosen to highlight the differing nature of individual practice, allowing comparisons between qualitative and quantitative projects to be explored.

Alongside the experiential learning will be a reflective element, which will focus on issues relating to client, consultant relations and implementation of management science, as well as addressing more conceptual issues relating to problem structuring, modelling, data collection, and choosing and mixing methods in the light of your growing experience.

Professional and ethical considerations will be highlighted, introducing you to the areas of agreement and debate within the profession. This module will also include an individual or small group project, where you'll select a technique or method they haven’t previously studied to research in more depth, mirroring professional development that they will undertake in practice. This component of the module will be managed through learning contracts.

This module builds upon your understanding of information systems. It'll provide you with the opportunity to develop analytical approaches for mining data using commercial software that'll be intellectually challenging and useful.

This module focuses on the methods used for mining data, complementing the other Honours modules that provide business context and processes.

Identifying and managing risk is a fundamental skill required by managers. Many models exist for supporting risk assessment and this is a major area of interest within the Management Science department.

This module will introduce you to the general concepts of risk and common measures used as well as considering ways of modelling and interpreting technical risk within the context of managing complex systems in areas such as transportation, aerospace, health.

It'll develop knowledge and skills introduced in years 1-3 in operations, statistics and modelling modules by integrating and extending them within the context of risk assessment.

This module investigates the application of sophisticated business technology systems to the management and, more particularly, integration of business processes.

In doing so, it builds directly on the knowledge and skills acquired as part of Management of Business Processes and, in a more indirect manner, on modules like Technological and Organisational Innovation, Information Systems in the Knowledge Economy, and Information Systems Support for Managers.

This module seeks to explore the inter-relationship that exists between a theoretically grounded understanding of technology and its effect on how modern organisations adopt such technology through an increasingly changing and competitive environment. This module will build upon skills gained in previous years, whilst allowing students to generate their own knowledge through rigorous class discussion and presentations.