University of Edinburgh

The course provides an introduction to selected genres of Celtic literature from the early modern and modern periods, and an understanding of the social and historical background that gave rise to the texts studied. Two strands make up the course, one dealing with the Scottish Gaelic tradition and the other looking at Early Modern and Modern Irish literature. English translations are used throughout the course, and no knowledge of the original Celtic languages is required. The course is aimed at students who have successfully completed Celtic Civilization 1A and 1B, as well as Heroes, Wonders, Saints and Sagas: Medieval Celtic Literature in Translation, but it is also open to anyone who has taken a course in a literary or historical or similar subject at university level and wishes to explore the Celtic tradition. The course does not provide a comprehensive survey of the two literatures studied, but rather to examine in greater depth certain periods or themes or genres which are characteristic of the tradition, which offer cross-cultural comparisons within the Celtic world, and which are amenable to study through translation. For history students, the course offers insight into the nature and working of the two literary traditions; for literature students, enhanced understanding of the social and political background to the selected parts of Scottish Gaelic and Early Modern and Modern Irish literature; for students of Celtic Studies, the opportunity to range widely in the early modern and modern fields.

The course looks at the way assets are valued in financial markets. It considers interest rates and the pricing of fixed-income bonds, stock market prices and returns, stock market risk and the influence of risk on the pricing of shares, and the characteristics and pricing of financial futures and options. The course also covers some aspects of company finance theory. These include business investment decisions, sources of finance, the cost of capital, the financial structure decision, and the dividend decision.

This course develops a rigorous understanding of core economic models and analysis, together with an ability to apply the analysis in a variety of contexts. It looks at the theory of the firm and market structure, factor markets, externalities, the role of government and general equilibrium, with applications to monopoly and oligopoly, stock markets, property rights and public goods. Along with two economics lectures each week, a third lecture focuses on mathematical techniques including constrained optimization. Students with a weak math background need to be prepared to work at developing their math skills.

The design and implementation of efficient, effective, and user-friendly computer systems, including software objects and physical internet-enabled things, depends upon understanding both the technology and its users. Only then can designers be confident that these information appliances will be properly matched to the skills, knowledge, and needs of their users. The study of human-computer interaction (HCI) seeks to combine perspectives and methods of enquiry drawn from disciplines such as interaction design, psychology, and sociology with the tools, techniques, and technologies of computer science to create an approach to design which is both relevant and practical.

Topics include Fourier analysis: Fourier series, Fourier transform, Dirac delta function, sifting property, Fourier representation, convolution, correlations, Parseval's theorem power spectrum, sampling; Nyquist theorem, data compression, solving ordinary differential equations with Fourier methods, driven damped oscillators, Green's functions for 2nd order ODEs, partial differential equations, PDEs and curvilinear coordinates, Bessel functions, and Sturm-Liouville theory. Topics for probability and statistics include concept and origin of randomness, randomness as frequency and as degree of belief, discrete and continuous probabilities, combining probabilities, Bayes theorem, probability distributions and how they are characterized, moments and expectations, error analysis, permutations, combinations, and partitions, Binomial distribution, Poisson distribution, the Normal or Gaussian distribution, shot noise and waiting time distributions, resonance and the Lorentzian, growth and competition and power-law distributions, hypothesis testing, parameter estimation, Bayesian inference, correlation and covariance, and model fitting.