This module introduces students to a broad outline of political, socio-economic, cultural and intellectual developments in Europe between the end of the...

Age of Revolution: European History 1815-1870 (HIST0197)

This module introduces students to a broad outline of political, socio-economic, cultural and intellectual developments in Europe between the end of the Napoleonic period and the Unifications of Italy and Germany. Our approach will be both comparative and transnational, emphasising trends that marked the experience of Europe as a whole. While the lectures offer a general survey of European history in the period, classes will investigate different aspects of political and social change, with particular focus on the European Revolutions of 1848, understood as a key experience of political modernity.

This module deals with strategic management issues related to running a telecommunications operating company [Telco], enabling delegates to appreciate the...

This module deals with strategic management issues related to running a telecommunications operating company [Telco], enabling delegates to appreciate the business perspectives of telecommunications both in the UK and globally. Emphasis is on providing an understanding of the

interactive nature of the forces impacting on the performance of Telcos.

Aims - This module aims to provide an introduction to the statistical aspects relating to the design of experimental and observational studies, and to...

Statistical Design of Investigations (STAT0029)

Aims - This module aims to provide an introduction to the statistical aspects relating to the design of experimental and observational studies, and to introduce associated methods of statistical analysis. It is intended for students registered on the Masters degree programmes offered by the Department of Statistical Science, or jointly with other departments.

Objectives - On successful completion of the module, a student should have an understanding of the basic ideas of experimental design and observational studies; should be able to analyse data from a variety of experimental designs by the analysis of variance; should be able to assess the appropriateness of various sampling schemes and perform appropriate analyses.

Applications - this module addresses the issues of what data are needed to answer a particular substantive question, and conversely what questions can reasonably be answered using data that may be available. These issues are fundamental to quantitative analyses in all application areas.

Content - Principles of experimental design: planning of experiments, comparative experiments, common designs (completely randomised, randomised blocks, Latin square, factorial experiments, nested, fixed and random effects), associated analyses of variance in the R software. Observational studies versus experiments: problems of bias, confounding, difficulty of causal interpretation. Observational studies: planning, matching, adjusting for confounding variables, cohort studies, case-control studies, data analysis. Sampling: target and sampled populations, finite populations, simple random sampling, stratification and cluster sampling, ratio and regression estimators.

Key texts - Available from ReadingLists@UCL.