Applied Statistics
The collection, management, analysis, and interpretation of data, using statistical tools, with the aim of evaluating the effectiveness of policies
Type
Functional
Competency Area
Public Administration
Levels
Understands the basics of applied statistics in public policy
Describes the policy problem, the extent, characteristics and factors associated with it
Aware of the quantifiable objective of statistical analysis (eg: aim of the policy, milestones, project costs, etc.)
Suggests use of data visualization to discuss the tools, techniques, and strategies to create captivating graphics for policy audiences
Recognises the importance of explaining complex concepts to diverse stakeholders (eg: public, professionals, political leaders, etc.)
Collates relevant information for statistical analysis
Gathers data (if it exists) on the policy problem or designs a data collection process of the variables pertinent for analysis of the problem
Demonstrates technical knowledge of statistical and inferential reasoning, probability theory, etc.
Develops a storyboard and uses software to map out the points for visualisation
Discusses the statistical outcomes with policy communication managers to guide analysis by specific, substantive program, and policy interests
Develops statistical models and tools for analysis
Establishes a data collection methodology (secondary data, primary data, experimentation, etc.) based on the purpose of analysis (research question)
Formulates statistical models (eg: regression analysis, difference-in-difference, etc.) using advanced statistical computing techniques (eg: knowledge of programming languages like R and Python; experience with the SAS software suite; an understanding of SQL database languages, etc.)
Illustrate the statistical outcomes through visualisation tools (eg: Datawrapper, Socrata, BetterWorld Flux, etc.)
Assembles reports and presentations to ethically communicate statistical outcomes in terms of policy changes, change in magnitude of interventions, etc.
Administers the communication of statistical outcomes
Verifies the accuracy and efficiency of the data collection through high-frequency checks, etc.
Promotes the application of statistical analysis in the evaluation of public policies in various fields including social sciences, economics, health sciences, population studies etc.
Incorporate feedback from the audience, on their understanding of the interpretation of the analysis, to update the analysis dissemination strategies
Rationalises valid conclusions from statistical analysis and ethically communicate them to diverse stakeholders and leaders