Understanding, Utilising and Evaluating Government Statistics G (10337.1)

This unit focuses on the use of statistics and data analysis to inform economic policy making and policy analysis. The unit aims to increase participants' awareness and literacy in statistical and data analysis so that they can be informed and critical consumers of these forms of analysis, and so that they can ensure that analyses are used appropriately to inform best practice in using evidence in policy.

The unit is organised into three modules:
Statistical Language and Data Analysis - explores basic research methods, and how to perform simple descriptive statistics operations. Participants learn to understand statistical concepts and terminology, and to analyse, interpret and evaluate statistical information.
Using Statistics for Evidence-Based and Fast Policy-Making - examines the concept of evidence-based policy making and what this means in the context of economic policy. It examines how good statistics can enhance policy decision making, and how statistics can inform 'good enough' policy making. Explores newer methods for doing policy, such as big data analysis, qualitative comparative analysis, randomised control trials.
Data Evaluation and Communication - covers the ingredients of best practice in program and policy evaluation, including new methods for data analysis and visualisation. This module also explores the challenges of strategic communication and policy messaging when complex statistical information underpins policy.

Learning outcomes

On successful completion of this unit, students will be able to:
1. Understand and analyse up-to-date statistical analysis common in APS work environments, including cutting-edge techniques;
2. Utilise data and statistical information critically, to inform better evidence-based policy making, to solve real-world problems facing Australia;
3. Think broadly about the opportunities that statistics and data analysis make available to graduates as APS employees can be utilised to understand and solve issues in their work environment;
4. Communicate strategically to help others of different cultural or professional backgrounds to understand complex data and information in ways that leads to better policy outcomes;
5. Engage with new ideas, new technologies, and new thinking about how to analyse complex social problems; and
6. Work collaboratively to solve complex problems.

Graduate attributes

1. UC graduates are professional - communicate effectively
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - behave ethically and sustainably in their professional and personal lives
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas
3. UC graduates are lifelong learners - evaluate and adopt new technology
4. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing - apply their knowledge to working with Indigenous Australians in socially just ways
4. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing - communicate and engage with Indigenous Australians in ethical and culturally respectful ways

Skills development

In this unit, students are not expected to have prior skills in data analysis. The unit does not seek to teach advanced statistical analysis skills. Instead, it seeks to build skills that enable students to:

• have familiarity with a number of major datasets 
• critically evaluate the quality and useability of different data sets and different types of data
• understand the opportunities and limitations associated with different types of data, including qualitative and quantitative data
•  implement data ethics and integrity principles to ensure data are collected, analysed and reported in ways that respect the rights of all people and contribute to positive outcomes
• critically analyse the way data are drawn on to make claims in documents such as policy briefs
• understand different approaches to data analysis and modelling and their pros and cons
• produce descriptive data analysis and visualisation that applies key principles of good data visualisation.

Students are expected to have a laptop available to work on during classes, with Microsoft Excel accessible on it. 

Corequisites

None.

Assumed knowledge

None.