Assessment in the module takes the form of an online software skills test (worth 10% of the final mark) and a final written exam (worth 90%).
MANG6003 aims to develop statistical reasoning. Via a series of examples and activities, students are introduced to the idea of probability modelling and how it can be applied to aid decision making in uncertain situations, which are frequently encountered in organisations. On successful completion of this module, students should be able to collect relevant data and summarise the main features of an uncertain situation, to identify standard problems and analyse them with the correct statistical tools, to process and analyse data in a statistical computer package, to understand the risks involved in a decision which involves uncertainty, and quantify such risks. Students should also develop problem solving skills, modelling skills, become familiar with a standard statistical computer package (SPSS), and be able to interpret and critically evaluate statistical results.
The module introduces some widely used quantitative approaches for characterizing uncertainty and risks in finance and management problems. The aim of the module is to introduce a number of widely used techniques for uncertainty and risk management and provide an understanding of how they can be used in practice.
This module develops analytical skills required for the final year Honours Project, scientific research in general, and your future career. The major skills are computer literacy and graphical presentation, understanding of scientific method and hypothesis testing, a few simple mathematical concepts, and basic methods of statistical analysis, including non-parametric tests, analysis of variance and data modelling.
The module will provide an opportunity for students to use A-level mathematical skills in studying Economics, Econometrics, Actuarial Science, and Management Sciences throughout their degrees. Pre-requisite for ECON2041 One of the pre-requisites for MATH3063, MATH3085
This module provides you with the opportunity to engage with econometrics theory focusing, in particular, on analysing financial markets and firms' investment and financing decisions. The module will systematically prepare you with the necessary skills to undertake quantitative research using both advanced theoretical knowledge and implementations using econometric software.
This module introduces you to quantitative research methods within the social sciences. The module is aimed at providing a firm understanding of the fundamental principles of quantitative analysis up to bivariate analysis, and a good foundation of knowledge of quantitative methods and their application to data relevant to disciplines across the Social Sciences, particularly Gerontology. You will learn about the analysis and data manipulation of quantitative data through a combination of online lectures, online exercises using SPSS, assessed coursework, tutorials, and individual study and practice. The module assumes no prerequisite knowledge of quantitative analysis and SPSS.
This module offers a more advanced training in quantitative research methods within the social sciences. The module is aimed at providing a deeper understanding of the fundamental principles of quantitative analysis, and a solid foundation of knowledge of quantitative methods and their application to data relevant to disciplines across the Social Sciences, particularly Gerontology. You will learn about a variety of regression analysis methods through a combination of online lectures, online exercises using SPSS, assessed coursework, tutorials, and individual study and practice. The module assumes prerequisite knowledge of statistical inferences, bivariate analysis, and SPSS.
The aim of this module is to provide an overview of advancement of quantum devices and technology in line with the development of nanoelectronics and nanotechnology. Students will gain knowledge of basic quantum mechanics and how the quantum mechanics are playing a key role in the state-of-the-art nanoelectronics. Then they will become also familiar with quantum information processing including quantum computing and quantum communication technologies.
The aim of this module is to provide an overview of advancement of quantum devices and technology in line with the development of nanoelectronics and nanotechnology. Students will gain knowledge of how the quantum mechanics are playing a key role in the state-of-the-art nanoscale semiconductor devices. They will become also familiar with devices that can realise quantum computing, quantum communication and quantum sensing. Quantum photonic and optomechanical devices, and quantum materials will be also covered.
Quantum information combines information science with quantum effects in physics to study of how to process and transmit information using quantum systems. This includes quantum computation, quantum teleportation and quantum cryptography. Quantum metrology is closely related, but focuses on using quantum effects to make high-resolution and highly sensitive measurements of physical parameters such as magnetic and gravitational field strengths. The course starts by revising the postulates of quantum theory with a quantum information flavour discussing how to store, process and read information using quantum systems. We will then study applications in quantum communications, quantum algorithms and quantum sensors.
Physical Chemistry is concerned with the application of physics to the study of chemical systems. Through physical chemistry one can understand and predict the behaviour of chemical systems, thereby allowing these systems to be optimised. This module provides a description of the basics of molecular spectroscopy and discusses several molecular spectroscopy techniques by focusing on the information content they provide. The basics of spectroscopy are discussed through quantum mechanical concepts thus building up the understanding of the microscopic world in the framework of quantum theory.
While coherence phenomena have long been familiar in the context of light waves, their manifestation in the context of matter waves is an exciting development of modern quantum science. This course aims to introduce the basic concepts needed to understand Quantum coherent phenomena, and the relevant experiments to probe such properties. We will study classical as well as quantum correlations which can be properties of light and matter. We will start briefly revisiting classical electrodynamics and quantum mechanics. We will then introduce the concept of photon, discuss photon statistics and noise, meet correlation functions and discuss relevant interferometry experiments. We will then discuss non-classical coherent and squeezed states such as Fock states. We will then discuss light-matter interaction as in cavity-QED. Finally, some applications of coherent light and coherent matter may include the discussion of examples such as Bose-Einstein condensation, quantum entanglement as well as selected topics from quantum communications, decoherence theory and quantum computing. The approach in this lecture is rather phenomenological, while still introducing the typical mathematical tools to evaluate coherence and to describe the electromagnetic field in a quantum formalism. We hope that this will provide students with an ideal basis to understand coherent phenomena in all kinds of physical systems and provide an introduction to the field of quantum technologies.
