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*This is a compulsory module for students registered on the Masters of Public Administration (MPA) programme and is not available as an optional module.

The past twenty years have seen an exponential growth in the use of quantitative methods and data analysis in all areas of social and natural sciences. Within the scope of public policy, this has dramatically changed the way important decisions are made in the 21st century and the methods which are used that lead to those decisions. A new reliance on data analysis and AI has led to a very large increase in demand, from all sectors, for people who are able to understand, summarize, analyse, and interpret quantitative information in a meaningful and useful way. Two key ingredients to forming optimal public policy, and understanding risk are: i) the data, which sometimes takes a secondary role to the sophistication of statistical methodology and can lead to mis-informative policy advice, and ii) the appropriateness of methodological approach chosen by the researcher to analyse the data.ÌýÌý

This course will briefly review some data quality/measurement issues, but our primary focus will be on introductory methodological approaches to analysing and interpreting data for public policy purposes. In order to achieve this will require building some technical foundations which will allow students to present compact, streamlined, and informative analysis that weeds out any irrelevant information and sells a key message. As managers, this course will also give students the ability to critically assess the underlying methodology and quality/ comprehensiveness of the data used to reach public policy decisions and interpret it in a meaningful way.Ìý

Many of the lectures in this course will comprise computer labs using statistical software (R/Stata), however students are not expected to have any background in applied or theoretical statistics. R software is available free online, and Stata can be accessed with a Ïã¸ÛÁùºÏ²Ê account. All data files and code will be available on Moodle. The purpose of these seminars is to provide a basic tool set for practical analytical work on real world policy issues. These will also equip students with the skills and tools to conduct independent statistical analysis upon completion of the course.ÌýÌý

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By the end of this module, students should:

• Be able to critically evaluate the quality and appropriateness of data used in public policy analysis.
• Be familiar with, be able to manual calculate, explain, and generate graphics, for meaningful statistics which summarize the characteristics of large N datasets.Ìý
• Be able to efficiently analyze and interpret public policy data in an appealing, meaningful and compact way.
• Be able to run and accurately interpret bivariate/multivariate and logistics regressions.Ìý