Aims: This two-day course has a core component that refreshes attendees’ skills in the analysis and interpretation of economic data, to support decision-making across business and the public sector. In addition, there is a component that can vary slightly with each delivery, depending on the specific needs of attendees; focusing on an updating of understanding around more recent approaches to data analysis. The sessions will be split between group work, lecturer delivery and a workshop-style approach depending on the tasks undertaken. The course allows attendees to refresh the skills required to be a critical reader of information and data, to ensure effective analysis and interpretation.
Attendees need to have some basic understanding of statistics and/or mathematics, but knowledge does not have to be up-to-date. The course is accessible even for those who have not studied data and statistics for some time.
More specifically, the two-day course will REFRESH, through a:
(i) Recap on understanding of the counterfactual in micro and macro contexts; and consider the strengths and weaknesses of key econometric techniques that attempt to estimate counterfactual outcomes.
(ii) Review of real-world examples of statistical research from business and government; asking, what does reliable evidence look like and what do we need to consider when using evidence to advise? Do we apply the same criteria for what is ‘good’ evidence in micro and macro studies?
(iii) Consideration of some key statistical series that feature in economic decision-making, and description of some of the common pitfalls made in interpretation.
Aims (i) to (iii) form a core component of the course, with illumination of these issues based on consideration of real-world examples wherever possible. To inform the focus of such discussion, attendees will be asked about their primary areas of practice prior to the course (i.e. work focused in certain sectors; analysis of market/customer data to inform business decision-making; macroeconometric or microeconometric modelling, etc.).
In addition to this core ‘refresh’, there are a number of additional topics that would be covered as an UPDATE component (two from the following list, decided in a ‘poll of attendees’ prior to the event - delivered as an overview of what the method aims to achieve, together with the main strengths/weaknesses);
- Machine Learning and Data Mining - Big Data: Analysis of Unstructured/Textual Data - Cost-Benefit Analysis - Evaluation: Overview of more Advanced Microeconometric Techniques - Forecasting: Overview of more Advanced Macroeconometric Techniques