Policy and Ethics of Data Analytics in the Public Sector

Deepen your understanding of the power and politics of data in the public sector, including how values ​​- in addition to data and evidence - are always part of public sector decision-making. In this course, you will explore common ethical issues surrounding data, data analytics, and randomized controlled trials in the public sector. You will also navigate and understand the ethical issues surrounding data systems and data analysis by understanding guidelines, codes of ethics, and professional guidelines. Using two technical examples, you will understand common ethical issues including participation bias in populations and how cross-sectional analysis is used to identify bias in predictive machine learning models. This course also serves as a capstone assignment for the Public Sector Data Analytics using R specialization, where you will conduct an applied policy options analysis using authentic data from a real-world example. In this assignment, you will examine data in a policy options analysis, create a visualization of the results, and make recommendations. All course assignments are completed in RStudio on Coursera, with no need to install any additional software. This is the fourth and final course in the Public Sector Data Analytics with R Specialization. This series is ideal for current or aspiring public sector professionals who want to gain the skills to effectively analyze government data. It is also ideal for current data scientists or students looking to enter the public sector.