PUBAFRS 4040 Public Sector Data Sciences and Management

Course Description

This course provides an orientation to the use of data for decision-making in the public sector. The emphasis in the course is how to use data in context — when organizations require the analysis of sophisticated data in order to achieve goals or priorities. Topics in the class include the following;

  1. Data use and decision making in the public sector;
  2. Legal and ethical framework for data use in the public sector;
  3. Use of data sciences in evaluation, planning, and performance reporting;
  4. Visualization techniques in public policy analysis;
  5. Geographic analysis; and
  6. Statistical tools to improve the use of data in decision making.

This course is designed to be an introduction for students interested in big data and public affairs. Data science methods will be described as utilized in the public sector. This requires both an understanding of the technical and methodological challenges of working with government data, but also the ethical and legal restrictions government places on data utilization. This class builds on some of the core content areas the Glenn College curriculum teaches. For example, the sequence of policy analysis and evaluation courses. Secondly it deepens knowledge in the decision sciences courses.

The course assumes a familiarity with statistics as in the GE required in Data Sciences. Students will get the most out of the class having already completed at least one course in statistical programming. The class is not a substitute for statistical training or programming skill.

Course Objectives

Upon completing this course, students will:

  • gain an understanding of the current technologies and ways government are using data to inform policy decisions;
  • be able to understand the structure and use of both administrative data and survey data for policy decisions;
  • learn the ethical and legal framework for using public data to carry out data science;
  • be able to conduct analyses of administrative and survey data on applied policy problems; and
  • be able to write a structured policy memo that informs policy decisions based on data analyses.