Associate Professor of Information
Assisting Public Sector Decision Makers With Policy Analysis
What You'll Learn
- Apply data analysis techniques to the core public sector principles of efficiency, effectiveness, and equity
- Develop analytical skills commonly used to analyze and assess policies and programs
- Answer questions policymakers ask such as “What should we do?” and “Did it work?”
5 Modules
20 Hours
4 hrs per module (approx.)
Rating
About Assisting Public Sector Decision Makers With Policy Analysis
Develop data analysis skills that support public sector decision-makers by performing policy analysis through all phases of the policymaking process. You will learn how to apply data analysis techniques to the core public sector principles of efficiency, effectiveness, and equity. Through authentic case studies and data sets, you will develop analytical skills commonly used to analyze and assess policies and programs, including policy options analysis, microsimulation modeling, and research designs for program and policy evaluation. You will also learn intermediate technical skills, such as Chi-squared tests and contingency tables, comparing samples through t-tests and ANOVA, applying Tukey's honest significant difference to correct for multiple tests, understanding p-values, and visualizing simulations of statistical functions to help answer questions policymakers ask such as “What should we do?” and “Did it work?” In addition, you will practice statistical testing and create ggplot visuals for two real-world datasets using the R programming language.
All coursework is completed in RStudio in Coursera without the need to install additional software.
This is the third of four courses within the Data Analytics in the Public Sector with R Specialization. The series is ideal for current or early career professionals working in the public sector looking to gain skills in analyzing public data effectively. It is also ideal for current data analytics professionals or students looking to enter the public sector.
Skills You'll Gain
- Data Analysis
- Policy Analysis
- Public Administration
- Public Policy Research
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Assisting Public Sector Decision Makers with Policy Analysis is part of the Data Analytics in the Public Sector with R certificate. This course equips learners with analytical frameworks and data-driven methods to support public policy and program decisions. You will explore policy typologies, evaluation methods, and simulation models while applying R-based analysis to real public sector datasets.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Course Schedule
Module 1: Policy Frameworks & Types of Policy Analysis
- Video: Introduction to Course 3: Assisting Public Sector Decision Makers with Data and Policy Analysis
- Reading: Course Syllabus
- Reading: Course Glossary of Terms
- Discussion Prompt: Meet Your Fellow Learners
- Reading: Help Us Learn About You
- Ungraded Lab: RStudio Lab
- Video: What is Policy and Why it Matters
- Video: Policy Typology
- Video: Facts About Public Policy
- Graded Assignment: Policy Typology Knowledge Check
- Video: Policy Typology—Examples
- Discussion Prompt: Policy Typology Application
- Video: The Policy Making Process
- Video: Policy Analysis: Definitions & Examples
- Video: Policy Analysis: Role of Data Analytics in the Policy Analysis
- Reading: Week 1 Optional Readings & Resources
- Graded: Week 1 Quiz: Policy Frameworks & Types of Policy Analysis
Module 2: Prospective Policy Analysis: What Should We Do? – Part 1
- Video: Framework for Policy Options Analysis—Part 1
- Video: Framework for Policy Options Analysis—Part 2
- Graded Assignment: Knowledge Check: Policy Options Analysis
- Video: Introduction to Inferential Statistical Analysis in R
- Video: Chi-squared Tests of Association
- Video: t-Tests of Difference in Means
- Graded Assignment: t-Tests of Difference in Means: Practice & Knowledge Check
- Video: ANOVA Models
- Video: p-Values & Simulation
- Graded: Week 2 Quiz: EDA & Inferential Statistical Analysis in R
Module 3: Prospective Policy Analysis: What Should We Do?—Part 2
- Video: Introduction to Policy Simulation Modeling
- Video: Examples of Policy Simulation Models
- Video: Economic Analysis in Simulation Modeling: Cost-Benefit Analysis
- Graded Assignment: Policy Microsimulation Modeling Knowledge Check
- Video: Economic Analysis in Simulation Modeling: Cost-Effectiveness Analysis
- Video: Dealing with Uncertainty: Sensitivity Analysis
- Video: Example of Sensitivity Analysis to Deal with Uncertainty
- Discussion Prompt: Point on Discussion: Are simulation models useful?
- Video: Policy Microsimulation: What is a Compartmental Model?
- Video: A Basic Tobacco Control Compartment Model
- Video: Tobacco Control Compartmental Model: Menthol Cigarette Example
- Reading: Week 3 Optional Readings & Resources
- Graded: Week 3 Quiz: Policy Microsimulation Modeling
Module 4: Program/Policy Evaluation: Did it Work?—Part 1
- Video: What is Program Evaluation and Why it matters?
- Reading: Raise Taxes on Tobacco
- Video: Types of Program Evaluation
- Video: Program Evaluation Framework
- Graded Assignment: Program Evaluation Knowledge Check
- Video: Focusing the Design and Gathering Credible Evidence
- Video: Example of a Research Design
- Video: Internal and External Validity: the Basics
- Video: Internal and External Validity: Examples
- Graded Assignment: Research Design Knowledge Check
- Video: Common Research Designs for Evaluation In Public Sector
- Video: Experimental Designs
- Video: Examples of Randomized-Controlled Trials (RCTs) of Public Programs
- Video: Coming Up Next: The DC Garbage Can Case Study
- Video: The DC Garbage Can Intervention: Data Analysis
- Video: The DC Garbage Can Intervention: Joining Data
- Graded Assignment: The DC Garbage Can Intervention: Practice & Knowledge Check
- Video: The DC Garbage Can Intervention: Wrap-Up
- Video: One More Thing For This Week: Random Assignment vs Random Selection
- Reading: Week 4 Optional Readings & Resources
- Graded: Week 4 Quiz: Program/Policy Evaluation
Module 5: Program/Policy Evaluation: Did it Work?—Part 2
- Video: Quasi-Experimental Designs
- Video: The Basics of Time-Series Design
- Video: Time-Series Design: Examples
- Graded Assignment: Quasi-Experimental Designs Knowledge Check
- Video: Coming Up Next: The Sicily Smoking Ban Case Study
- Video: The Sicily Smoking Ban Case Study: A Worked Example of Epidemiology
- Reading: Week 5 Optional Readings & Resources
- Video: Congratulations on Completing the Course!
- Reading: Post-Course Survey
Grading Policy
There are four quizzes in this course, with each quiz being worth 25% of your final grade. Learners must earn an overall grade of 80% in order to pass the class.
James B. Hudak Professor of Health Policy
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Intermediate Level
Some related experience required
