Students are provided with an understanding of functions, limits, and series, and knowledge of the basic techniques of differentiation and integration. Examples of functions and their graphs are presented, as are techniques for building new functions from old. Then the notion of a limit is considered along with the main tools of calculus and Taylor Series. Students will also learn how to add, multiply and divide polynomials, and will learn about rational functions and their partial fractions.

The exponential function is defined by means of a power series which is subsequently extended to the complex exponential function of an imaginary variable, so that students understand the connection between analysis, trigonometry and geometry. The trigonometric and hyperbolic functions are introduced in parallel with analogous power series so that students understand the role of functional identities. Such functional identities are later used to simplify integrals and to parametrise geometrical curves.

This course provides an introduction to microeconomics for students majoring in business-related degrees and delivers a range of important topics for understanding the business applications of economics relating to both consumers' and firms' behaviour.

This course extends ideas of MATH101 from functions of a single real variable to functions of two real variables. The notions of differentiation and integration are extended from functions defined on a line to functions defined on the plane. Partial derivatives help us to understand surfaces, while repeated integrals enable us to calculate volumes.

In mathematical models, it is common to use functions of several variables. For example, the speed of an airliner can depend upon the air pressure and temperature, and the direction of the wind. To study functions of several variables, we introduce rates of change with respect to several quantities. We learn how to find maxima and minima. Applications include the method of least squares. Finally, we investigate various methods for solving differential equations of one variable.

Business analytics focuses on developing new insights and understanding of business performance based on data analysis.

Designed to give you the kind of skills that are sought after in many organisations, this module introduces you to a range of quantitative techniques for collecting, analysing and interpreting data and develops your understanding of how to apply these techniques to management problems to draw practical conclusions. The module provides the foundations for statistical methods in follow-up modules.

The computing side of the module introduces the use of word processing, spreadsheet software for statistical calculations, and writing of management reports.

You will learn not only the fundamental analytical techniques, but also when and how to apply them to management problems and how to interpret the results. This module also involves you working as a junior business analyst on a simple but realistic case study and reporting results and conclusions to a fictional boss.

This module provides an introduction to the analysis and use of published financial statements and concepts underlying financial reporting by companies. It also considers the perspectives of various users and opportunities for creative accounting. The concepts and use of financial statements are placed within the current commercial context, so that you acquire an appreciation of the role of financial accounting.

This module introduces a variety of traditional and non-traditional ideas about management, followed by the theory and practice of team working and capability for management. The aim is to provide you with an essential understanding of the basic theories relevant to the management of work organisation and to enable you to identify and understand the limitations inherent within these theories.

Introducing the theory of matrices together with some basic applications, students will learn essential techniques such as arithmetic rules, row operations and computation of determinants by expansion about a row or a column.

The second part of the module covers a notable range of applications of matrices, such as solving systems of simultaneous linear equations, linear transformations, characteristic eigenvectors and eigenvalues.

The student will learn how to express a linear transformation of the real Euclidean space using a matrix, from which they will be able to determine whether it is singular or not and obtain its characteristic equation and eigenspaces.

During this Preparation for Internship module, you will learn about the competitive recruitment processes in the UK and the skills and expertise employers expect you to evidence; how to produce excellent CVs and cover letters; how to make an impact on application forms, what to expect at interviews and assessment centres.

You will be invited to attend our Placements and Internships Showcase at the start of the year where employers provide insights into their company and sector and highlight opportunities you could consider. They also share how they select successful applicants.

You will be shown the range of resources and support we offer in LUMS Careers and how that will continue throughout your year, in order to secure a suitable summer internship.

The aim of this module is to introduce the key elements of marketing as both scientific discipline and organisational practice. The module is designed around three themes which serve as a solid foundation for the second year module MKTG227 marketing Management Essentials and further marketing modules following this.

This module also aims to support students in the transition towards independent learning, and in the development of a critical and analytical approach to ideas and theories.

Probability theory is the study of chance phenomena, the concepts of which are fundamental to the study of statistics. This module will introduce students to some simple combinatorics, set theory and the axioms of probability.

Students will become aware of the different probability models used to characterise the outcomes of experiments that involve a chance or random component. The module covers ideas associated with the axioms of probability, conditional probability, independence, discrete random variables and their distributions, expectation and probability models.

To enable students to achieve a solid understanding of the broad role that statistical thinking plays in addressing scientific problems, the module begins with a brief overview of statistics in science and society. It then moves on to the selection of appropriate probability models to describe systematic and random variations of discrete and continuous real data sets. Students will learn to implement statistical techniques and to draw clear and informative conclusions.

The module will be supported by the statistical software package ‘R’, which forms the basis of weekly lab sessions. Students will develop a strategic understanding of statistics and the use of associated software, which will underpin the skills needed for all subsequent statistical modules of the degree.