Public Affairs 4040: Public Sector Data Sciences and Management
This is a sample syllabus to provide general information about the course and it's requirements. Course requirements are subject to change. This syllabus does not contain all assignment or course detail and currently enrolled students should reference the syllabus provided by their instructor. For a specific syllabus, please email us a request.
Learning Outcomes
By the end of this course, students should successfully be able to:
- Gain an understanding of the current technologies and ways governments are using data to inform policy decisions.
- Understand the structure and use of both administrative data and survey data for policy decisions.
- Conduct analyses of administrative data and survey data on applied policy problems.
- Be able to write a structured policy memo that informs policy decisions based on data analyses.
- Comprehend the ethical and legal framework for using public data to carry out data science projects.
Requirements and Expectations
A textbook may required for this course. Consult your instructor's syllabus for details.
- Class Memos: 30%
- Class Discussions: 15%
- Checklists: 5%
- Final Project: 50%
Description: You will answer questions about data science concepts, theories, and data analysis techniques in class memos. There will be five memos. Each one is worth 6 points, and will comprise 30% of the final grade. Late assignments will be subject to a point deduction: one late day results in a one-point deduction. Assignments handed in five days late or more will not receive any points.
Independent work: The questions in the memos are based on class readings, lectures, and programming practices. While you are welcome to work in study groups when learning class materials and doing exercises, it is essential to use your own words and code when answering the questions in the memos.
Description: Every three weeks there is a checklist (in a survey format) to fill out. Please report the readings, coding, and other activities you have done, as well as any feedback for the class. This is the primary way to track your progress in the class.
Independent work: You should fill in the checklist independently and express your own thoughts and opinions.
Description: You will complete a data science project independently in this class, including project design, data analysis, data visualization, final report, and presentation. There will be five submissions throughout the semester: 1) project proposal (10 points); 2) intermediate presentation (5 points); 3) draft paper and code (10 points); 4) final presentation (5 points); 5) final paper and code (20 points). The presentations will be held in class. Late submissions of the proposal, paper, or code will be subject to a point deduction: one late day results in a one-point deduction. Assignments handed in one week late or more will not receive any points.
Independent work: While you are welcome to work in study groups to receive peer feedback on your project and seek help for programming on websites such as StackExchange, it is essential to develop your own project idea, and write your own code and paper. As part of your submission, include your data files, code, presentation file (which could be PowerPoint, Tableau Workbook, or Jupyter Notebook), and paper. Ensure that your code has detailed comments and descriptions, and verify that your results can be reproduced. If you reference any research paper, report, methods, or code, be sure to cite them appropriately.