This module provides an overview of the breadth of earthquake engineering as a discipline, providing the most important knowledge and intellectual skills for students to be able to assess earthquake hazards and ground motions (shaking), and then to analyse and design structures for earthquake resistance. Particular attention is paid to performance-based seismic design and assessment of steel buildings. The module will start from the fundamental theory of structural dynamics and earthquake engineering. It will then gradually cover linear and nonlinear structural analysis methods and their application to simplified and rigorous performance-based seismic design and assessment of steel building structures. Relevant seismic design guidelines in Eurocodes will be thoroughly covered. It is emphasised that the course includes an introduction to aspects of structural dynamics relevant to earthquake engineering for students who lack this pre-requisite knowledge. The Module is based on a combination of Lectures (theory) and Computer Lab Sessions (computational implementation of the theory). It involves the use of the commercial software SAP2000 as well as MATLAB. Step-by-step tutorials for using the software and MATLAB will be provided. Computer lab sessions at the last four weeks will solely devoted to the design project carried out by the students. During all lab sessions, the Lectures will provide to students instruction and feedback on their progress towards the completion of their project. Overall the module consists of 20 lectures and 10 computer lab sessions.
This module will start by exploring the work of Johnnie To, a prominent Hong Kong crime film director, as the main example to study East Asian Noir, and to interrogate issues of genre and authorship, as well as the intersection of the local and the global. The second half of the module looks at noir examples from, South Korea and mainland China.
This course is intended as a beginner’s guide to marine ecological modelling. It is suitable for students across a broad range of academic backgrounds and does not assume a high level of prior mathematical knowledge or experience in coding. The course will give you the knowledge to better understand the strengths and limitations of published models and the skills to develop your own.
This module introduces students to the main branches of ecology by considering the various levels at which the subject may be studied: individuals, populations, communities and ecosystems. The aim of the fieldwork and practical sessions is to demonstrate how professional ecologists define and identify problems, how data are collected, and how results of ecological research are analysed, interpreted and applied to environmental and global issues.
This module explores human evolution in terms of physiological, social and cultural adaptations. It explores human ecology in the broad sense, combining not just cultural and social variability, but also physiological adaptations in past and present-day hunter-gatherers and great apes. These physiological adaptations are not just skeletal, but are also reflected in soft tissues and in surviving genotypes. We shall cover six main themes: different models of biocultural change; Human Behavioural Ecology; hominin energy budgets; brain size changes; dexterity, handedness and tool-use; social organisation over time and space. Evidence derived from primatology, ethnoarchaeology, ancient DNA, stable isotopes and Palaeolithic assemblages can be used to test models such as the Social Brain hypothesis, Daily Energy Expenditures, hominin thermoregulation and mobility/locomotion costs, and the applicability of different evolutionary mechanisms to change in the archaeological record (e.g. Lamarck versus Darwin). Lectures will be augmented by student-led seminars on key debates in palaeoanthropology and Human Behavioural Ecology.
This is a blended learning module to provide students with the basic tools and information necessary to embark in their third year dissertation modules.
The module will familiarise students with the parts of statistical distribution theory and statistical inference that are essential to a full understanding of econometrics and applied statistics. It will give student a thorough introduction to the theoretical concepts underlying modern Econometrics. It develops ideas presented in ECON1007 and ECON1011 and applies mathematical techniques from ECON1008.
The module will proceed from a review of known content (like matrix algebra, linear regression, hypothesis testing) to more advanced topics such as multiple linear regression, heteroscedasticity, restrictions in hypothesis testing, issues of model misspecification, and an introduction to big data techniques such as shrinkage methods to exploit large datasets for statistical inference. The module will thus equip students with fundamental methods for statistical inference on large datasets.
This module will familiarise students with the main concepts, methods and insights of microeconomic analysis, with a special focus on their possible applications and policy implications.
The module will provide a foundation in contemporary economic geography, focusing on the ways in which economic, political and social processes construct the profound diversity of modern economic life.
This module provides a comprehensive introduction to economics, covering both microeconomic and macroeconomic aspects. It analyses how fundamental economic concepts affect individuals, companies, and financial institutions and systems. It illustrates how core economic principles may be used to aid decision making and to guide behaviour.
The aim of this module is to equip you with some analytical and professional skills that will be useful in your economics degree and future careers. The module will also provide information about employability opportunities in your discipline, such as internships and careers fairs. It consists of three timetabled lectures per semester plus independent study via Blackboard at your own convenience. The average study time is 1-2 hours per week.
The aim of this module is to equip you with professional skills and knowledge that will be useful in your future careers, as well as when applying for graduate jobs. The module consists of up to three timetabled lectures per semester plus independent study via Blackboard at your own convenience. The timetabled lectures include guest talks on what employers look for when hiring graduates. The average study time is up to 1 hour per week.
This module supports the requirement for students to transition from the taught to the research element of the Integrated PhD in Economics.
This module gives an introduction into economic policy analysis that is based on empirical data. A range of economic policy questions covering different areas of economics will be presented. Policy recommendations will be derived using analytical economic concepts and analysis of empirical data. Students will be familiarised with basic methods of data analysis for economic policy.
