This core MPA module focuses on the tools and processes that contemporary governments at every level use to manage and implement policies and achieve results....

This core MPA module focuses on the tools and processes that contemporary governments at every level use to manage and implement policies and achieve results. It examines how leading governments in every part of the world implement policies and programmes; how they monitor; how they use data; how they learn; how they partner with business and civil society; and how they innovate.  

 

Throughout the module, students will have the opportunity to reflect on how governments are not only handling longstanding tasks such as distributing welfare or regulating companies but also how they are responding to increasingly complex challenges, from pandemics to climate change. 

 

The module links contemporary dilemmas to the history of government – from China, Rome and Persia two thousand years ago to 19th century administration and contemporary use of platforms.   It shows how governments are grappling with new tasks, such as the regulation of social media; and how they manage money, structures and processes to achieve results.  

 

Students will be introduced to the main tools and techniques of contemporary public management and governance, the rationale behind them, and their intended and unintended consequences.   We’ll also look at leading examples of public sector innovation and issues such as the management of risk.   In class students will be able to dive deeper into specific cases and to draw on examples from their own countries.  By the end students will have a firm understanding of how government works in the real world – and what the frontiers of effective government look like today. 

Aims - This module aims to introduce the statistical package R with particular application to statistical modelling and a selection of computational...

Aims - This module aims to introduce the statistical package R with particular application to statistical modelling and a selection of computational techniques. 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 be able to use the statistical package R to input, edit and manipulate data, produce appropriate graphics and implement statistical methods taught in other modules. In addition, the student should be familiar with some basic principles of programming, and should be able to carry out simple programming in R with application to a variety of computational and numerical techniques.

Applications - the generic programming skills acquired in this module are applicable across a wide variety of scientific disciplines as well as in the IT sector. More specifically, the R programming environment is gaining popularity among many research communities as well as in specialised areas of business and industry, such as finance and reinsurance, where non-routine statistical analyses are increasingly required. 

Content - Using R: expressions, assignments, objects, vectors, arrays and matrices, lists and data frames, functions, control structures, graphics. Efficiency considerations. Statistical modelling in R (in collaboration with STAT0028 and STAT0029): linear, generalised linear and non-linear modelling. Unsupervised learning: dimension reduction and clustering.  Computational techniques: function minimisation (in particular for mle’s and in non-linear modelling), quadrature, simulation (general methods, Monte Carlo).

Key texts - Available from ReadingLists@UCL.