Weeks per Term
Courses
Months
Learning Objectives
Students learn to judge the quality and limitations of data, choose appropriate analytical methods and explain what the findings mean. You’ll also evaluate how policies affect people, use behavioral insights to inform policy design and adapt recommendations as new information becomes available. Throughout the program, you’ll examine the ethical consequences of using data and analytical tools in public decisions.
Graduates of this program will be able to:
- assess and communicate the qualities, risks and uncertainties associated with data used in policy decision-making;
- evaluate the capabilities and limitations of different analytical techniques and policy design approaches, including those based on behavioral insights;
- anticipate and evaluate impacts of data-driven policy;
- design policy and public programs to address uncertainty and new information in policymaking contexts and;
- identify and evaluate ethical challenges emerging from the use of data and different policy design approaches to inform policy decision-making.
Course Breakdown
Online M.S. in policy analytics courses are designed and led by the same faculty who teach on campus at the Maxwell School. Courses are comprised of core requirements as well an elective course option.
Core Courses (27 credits):
This course introduces students to data management, wrangling, communication and visualization in the context of public policy and behavioral science as well as the technical tools necessary to do such work in an open and reproducible fashion.
Taught by Associate Teaching Professor Jack Reilly
Descriptive statistics (measure of central tendency, variation, bivariate association). Basic inferential statistics (point and interval estimation, hypothesis testing).
Taught by Associate Professor Sarah Hamersma
Development of quantitative tools for evaluating policies and programs. Expansion from bivariate to multivariate regression, including linear and nonlinear models, with techniques for assessing inequalities across subgroups and accounting for unobserved confounding factors. Prereq: PAI 721
Taught by Professor Robert Bifulco
Introduces students to using data for decision-making in the public sector. Equips students with the skills to navigate data-driven solutions for public issues by covering foundational concepts and basic data analysis skills.
Course covers opportunities and challenges regarding the use of artificial intelligence (AI) for policy design.
Taught by Associate Professor Tomás Olivier
Course provides an introduction to the policy process, focusing on new directions in policy process scholarship and evidence-based insights for practitioners.
Taught by Professor Saba Siddiki
Topics in moral philosophy, research ethics, ethics of machine learning, and philosophy of science relevant for ethical issues arising from the practice of data science.
Taught by Associate Professor Johannes Himmelreich
This course covers behavioral science theory and its application in the public sector. Evidence from empirical field experiments provides insights into the common mistakes policymakers make when they design policies. It also focuses on designing and evaluating effective behavioral policies.
Taught by Professor Leonard Lopoo
Develops analytical and computational skills for policy analysis. Covers the economics of uncertainty and information, including implications for policy design, and develops professional grade skills for building and analyzing large, complex datasets in a clear, reliable and reproducible way. Prereq: PAI 721
Taught by Professor Pete Wilcoxen
Elective Course Options (3 credits):
Students can choose an open elective from any online graduate course in the Public Administration and International Affairs Department, the Maxwell School or elsewhere at Syracuse University with the support of their academic advisor. Examples of online elective graduate courses the department offers regularly include, among several others:
- PAI 755: Public Administration and Democracy
- PAI 746: Ethics and Morality in Public Affairs
- PAI 601: Fundamentals of Conflict Studies
- PAI 730: Strategic Planning for Public Management
- PAI 734: Public Budgeting
- PAI 781: Social Welfare Policy
Sample Schedule Breakdown
The online M.S. in policy analytics program consists of 30 credits which can be completed entirely online in as few as 20 months of part-time study.
See the sample schedule below to help you better visualize how you may move through the online M.S. in policy analytics program. This is only an example of a possible course sequence.
You can adjust your course load and sequence with guidance from your academic advisor. There is no mandatory sequence you are required to follow, although some courses do have prerequisites.
Term 1
- PAI 741: Data Wrangling and Visualization for Public Policy
- PAI 760: Public Policy Process
Term 2
- PAI 721: Introduction to Statistics
- PAI 724: Data Driven Decision Making
Term 3
- PAI 722: Quantitative Analysis
- PAI 778: Artificial Intelligence Applications in Policy Design
Term 4
- PAI 796: Philosophy and Ethics of Data Science
- PAI 798: Behavioral Public Policy
Term 5
- Open Elective
- PAI 789: Advanced Policy Analysis
Online Course Format and Calendar
Online courses for the M.S. in policy analytics program maximize flexibility for working professionals while prioritizing active learning with your peers. Unlike the traditional classroom model, our program puts you in control of when you learn. Lectures are pre-recorded and delivered in short segments interspersed with assessments to reinforce learning.
Each week you'll work through approximately 70 minutes of on-demand course material, available 24/7, at your own pace. You'll join your peers for a weekly live, 90-minute discussion with faculty via Zoom, typically held Monday through Thursday evenings from 7-8:30 p.m. ET.
Students can choose how many classes to take per term (most take two to complete the program in 20 months) and should plan to spend up to seven hours per week per course, including lectures, readings, assignments and the live session.
The learning platform accommodates different learning styles with features including adjustable video speed, interactive transcripts, a calendar and progress tracking.
Most courses run 15 weeks (including exam week) and follow the traditional semester calendar across three terms: spring, summer and fall. Most courses are offered multiple times a year and are taught by the same faculty who teach in our residential programs.