BA Joint Hons Economics, Mathematics & Statistics

Topics

First Year aims to help you make the transition to the university context. Semester 1 is the Thematic Semester: The World of Business Today and covers topics such as:

• Social-Ethical-Environmental Governance (SEEG)
• Business Ethics
• Disruptive Technologies

Semester 2: Functional Semester: Organisations Today covers topics such as:

• Creativity & Responsibility
• Marketing & Sustainability across Domains

Class description

The first year of the programme is centred on the construction of knowledge in classroom setting with theoretical constructs developed. For each topic we’ve recorded a video by a Strathclyde academic who is a leading expert in the field.

You’ll watch these lectures in advance of each session and complete a pre-sessional activity. The pre-sessional work then forms the basis of team based activities work in the classroom (groups of 50 and teams of six-seven) where you develop an agreed understanding of the topic and present this to the group.

The feedback gained from this activity then feeds directly into the assessment for the block. You’ll complete 16 assignments in the two semesters of the class.

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, all demonstrated in application to practical problems including solving basic first and second-order differential equations.  

Topics

Semester 1 topics include:

• Working in Business Organisations
• Working Business Research & Consultancy
• Working Internationally
• Working in the Third Sector
• Rhetorics & Oratory

Semester 2 is about developing the proposal of MDP3; with a presentation and a final report.

Class description

The second year concentrates on developing understanding through industry-specific contextualisation. Sessions are weekly and three hours in length.

The sessions are thematically linked to the pathways for individualised experience in third year whilst also drawing on the theoretical knowledge developed in MDP 1. In order to develop understanding, organisations will deliver a half-day session. This consists of a one hour plenary introduction where the company and case study are introduced. This is followed by the group sessions where you undertake activities in relation to the case study set by the company.

This class 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.

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

This class 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.

The third year of centres on individualised experience in an organisational context through one of the following pathways:

• Internship/Charities - gain practical experience in a private or third sector organisation. You need to negotiate and locate your own organisation and experience – this is one of the key learning points of the pathway.
• Research and consultancy - a facility for local small businesses to gain from the experience and expertise of those within SBS. You work on two live business consultancy projects (one in each semester) and, as a team of 6, develop solutions and strategic initiatives for the local SME economy.
• International experience – only available for students who are undertaking an international exchange for either one semester or full year.
• Vertically Integrated Projects - working on a cross-faculty basis to research longitudinal projects (including the ‘Bill Gates Toilet Challenge, Solar Panels for Gambia and Enterprise in Schools) you work with a team of students from all levels of study (first year undergraduate to final year PhD) to further the work of the project.

In addition, you’re required to undertake a social responsibility element (this accounts for one quarter of the overall workload).

These have been designed to provide support to the Curriculum for Excellence and the Widening Access to Higher Education programme. There are no formal classes for MDP3 although there is pathway support with the pathway leads and tutor support.

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 class 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

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

Here 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. It'll 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.

You'll 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. In addition to applications of the methods to financial and economic systems, including modelling, data analysis, and forecasting.

In the third year econometrics class you’ll have learned about regression in both a cross-sectional data and time series data context. This class extends that knowledge in three ways.

First, for cross-sectional data, the class deals with regression techniques where the dependent variable may be restricted or limited in some way. In such cases, the regression model as taught in the third year class is not appropriate; this class develops models which are similar in spirit to the standard regression model, but can handle all of these cases.

A second purpose of Applied Econometrics is to develop regression methods which can be used when you have panel data - consisting of both cross-sectional and time-series dimensions.

Third, the class will build on the introduction to the econometrics of time series data developed in this class by developing two classes of models.

This class gives a balanced view of the role of finance in promoting long-run economic growth, but also booms and busts. The nature and role of financial intermediaries will be introduced, and, afterwards, formally addressed in a simple aggregate growth model. Empirical evidence will be examined, before turning to the specifics of micro-finance. The importance of financial globalisation will also be investigated. Finally, the rest of the class will be devoted to deciphering the causes and consequences of the current financial crisis.

Behavioural Economics offers alternative theories that merge psychological insights with economic theory and are based on experimental and other evidence, that attempt to provide a better explanation of real-world behaviour.

This class is concerned with exploring these new behavioural theories with the aim of providing you with an expanded toolkit with which to approach ‘real-world Economics’ that is based on the burgeoning Behavioural Economics literature that has emerged over the past two or three decades.

After studying this, you should be able to extend much of your previously-learned knowledge in Microeconomics in various directions that take into account more realistic ways of modelling how individuals behave.

The class provides you with an introduction to natural resource, environmental and energy economics and policy. It focuses on the contributions of economics to understanding environmental, energy and resource problems, their causes, and the design of effective public policies to counteract them.

This class 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.

Here 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 class 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 class will provide you with a range of applied statistical techniques that can be used in professional life.

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 class will present the main results in Functional Analysis, give an introduction to linear operators on Banach and Hilbert spaces and study applications to integral and differential equations.

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.

You'll be presented with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.

Here you'll learn the application of mathematical models to a variety of problems in biology, medicine, and ecology. It'll 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, and 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.

We'll introduce you to general continuum theory with applications to Newtonian and non-Newtonian fluids and elastic materials.

We'll provide you with a basic mathematical understanding of modern approaches to optimisation and the calculus of variations.

Here you'll develop approaches to understanding complex or random systems in or out of equilibrium, based on ideas from statistical mechanics that incorporate familiar concepts and methods from neighbouring subjects like classical mechanics and probability and statistics.

You'll also be able to describe, through various examples and techniques, how macroscopic properties of systems arise from the ensemble action of many microscopic ingredients, and, specifically, how deterministic 'laws' may arise from basic randomness of a system with many variables or degrees of freedom. Fundamental examples include Brownian motion and the ideal gas.

We'll introduce mathematical models which arise in epidemiology and population dynamics, and help you develop techniques for analysing the qualitative behaviour of the associated dynamical systems.