England.

# BSc (Honours) Mathematics and Statistics - Learning outcomes

## Educational aims

This degree introduces you to mathematical and statistical concepts and thinking, and helps you to develop a mathematical and statistical approach. You should achieve

• familiarity with the key ideas of probability and statistics (particularly basic distributions and inference, linear and generalised linear models, time series, multivariate statistics, Bayesian statistics, applied probability including Markov processes), and an ability to apply their main tools to a range of applications
• familiarity with the essential ideas of pure mathematics (particularly analysis, linear algebra and group theory), and the ability to recognise a rigorous mathematical proof OR ability to use the main tools of applied mathematics (particularly Newtonian mechanics, differential equations, vector calculus, numerical methods and linear algebra)
• ability to model real world situations and to use mathematics and statistics to help develop solutions to practical problems
• ability to follow complex mathematical and statistical arguments and to develop brief arguments of your own
• experience in the study of mathematics and statistics in some breadth and depth
• ability to understand some of the more advanced ideas within mathematics and statistics
• development of your capability for working with abstract concepts
• ability to communicate mathematical and statistical ideas, arguments and conclusions effectively
• the skills necessary to use mathematics and statistics in employment, or to progress to further study of mathematics and/or statistics
• ability to use modern mathematical and statistical computer software packages.

## Learning outcomes

### Knowledge and understanding

On completion of this degree, you will have knowledge and understanding of

• a range of simple and more advanced methods for analysing statistical data (including medical applications data, time series data and multivariate data), working with probability models and carrying out statistical inference (including in particular methods for linear and generalised linear models, and Bayesian methods)
• one of
(a) the elements of linear algebra, analysis and group theory
(b) the concepts behind the methods of Newtonian mechanics, differential equations, multi-variable functions, vector calculus, linear algebra, numerical analysis and mathematical modelling
• a selection (depending on what you study at earlier stages of the qualification) of advanced topics including
(a) pure mathematics: graphs, networks, complex analysis
(b) applied mathematics: advanced calculus, fluid mechanics, advanced numerical analysis, partial differential equations, deterministic and stochastic dynamics.

### Cognitive skills

On completion of this degree, you will have acquired ability

• in mathematical and statistical manipulation and calculation, using a computer package when appropriate
• to assemble relevant information for mathematical and statistical arguments and proofs, and/or judgment in selecting and applying a wide range of mathematical and statistical tools and techniques
• to construct appropriate mathematical and statistical arguments of your own
• to reason with abstract concepts
• to create appropriate mathematical and statistical models and draw justifiable inferences
• in qualitative and quantitative problem-solving skills.

### Practical and/or professional skills

On completion of this degree, you will be able to demonstrate the following skills:

• apply mathematical and statistical concepts, principles and methods
• analyse and evaluate problems (both theoretical and practical) and plan strategies for their solution
• be an independent learner, able to acquire further knowledge with little guidance or support.

### Key skills

On completion of this degree, you will be able to demonstrate the following key skills:

• read and/or listen to documents and discussions that have mathematical or statistical content, with an appropriate level of understanding.
• communicate information having mathematical or statistical content accurately and effectively, using a format, structure and style that suits the purpose.
• prepare mathematical or statistical content for a range of purposes, which may include writing for both specialist and non-specialist audiences; writing reports on mathematical or statistical experiments or models; producing and/or delivering a presentation on a mathematical or statistical topic. Preparation of some content may require working collaboratively with others on projects.
• exhibit a high level of numeracy, appropriate to a graduate in mathematics and statistics.
• use information technology with confidence to acquire and present mathematical and statistical knowledge, to model and solve practical problems and to develop mathematical insight.

## Teaching, learning and assessment methods

Knowledge, understanding and application skills, as well as cognitive (thinking) skills, are acquired through distance-learning materials that include specially written module texts, with practice exercises, guides to study and mathematical handbooks, comprehensive websites and a range of multimedia material (including computer software). Modules at higher levels build on the foundations developed in pre-requisite modules at lower levels.

You will work independently with the distance-learning materials, while being supported by a tutor. You will be offered the opportunity to attend online tutorials, which you are strongly advised to attend. You are also encouraged to interact with other students, for example via moderated online forums.

Written tutor feedback on assignments provides you with individual tuition and guidance. Your learning is further assessed through examinations and projects. Generally, you are permitted to bring the module handbook into examinations, thus reducing the need for memorisation, and concentrating on your ability to apply concepts and techniques and express them clearly and coherently. Your module results will be determined by your performance on both the assignments and the examination/project. For each module the final result will be based on a combination of the examination (or end-of-module assessment) score and the score obtained on (or engagement with) the continuous assessment. In some cases there is a threshold on individual components.