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.
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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.
Course 3 of 4 in the Data Analytics in the Public Sector with R Specialization.
Syllabus
WEEK 1
Week 1 | Policy Frameworks & Types of Policy Analysis
Welcome to the third course in the Data Analytics in the Public Sector with R Certificate— Assisting Public Sector Decision Makers with Data and Policy Analysis. This week, you will begin to develop a competent understanding of different Policy Frameworks and Types of Policy Analyses. You will also get to recognize the important role of data analytics in the policy analysis process.
WEEK 2
Week 2 | Prospective Policy Analysis: What Should We Do?—Part 1
Welcome to Week 2! This week will be your introduction to Prospective Policy Analysis to develop analytical skills to choose appropriate policy options, and develop skills in forecasting and policy simulation methods. You will learn first the steps in the policy options analysis process and then dive deeper into inferential statistical analysis in R.
WEEK 3
Week 3 | Prospective Policy Analysis: What Should We Do?—Part 2
Welcome to Week 3! This week you will continue learning about Prospective Policy Analysis to develop analytical skills to choose appropriate policy options, and develop skills in forecasting and policy simulation methods. You will learn about policy microsimulation modeling through authentic examples and case studies.
WEEK 4
Week 4 | Program/Policy Evaluation: Did it Work?—Part 1
Welcome to Week 4! This week you will dive into program and policy evaluation. You will learn first the basics of policy and program evaluation, the fundamentals of research design—the core of program evaluation, and the different research designs for you can use for program evaluation.
WEEK 5
Week 5 | Program/Policy Evaluation: Did it Work?—Part 2
Welcome to Week 5, the last week in this course! This week you will learn about the Quasi-Experimental Research Designs for program and policy evaluation. You will learn the basics of Time-Series Design and develop specific skills for data analytics.
