This course is part of the Data Analytics in the Public Sector with R Specialization

Christopher Brooks +1 more instructor

Offered By

Data Analytics in the Public Sector with R SpecializationUniversity of Michigan

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 4 in the

Data Analytics in the Public Sector with R Specialization

Intermediate Level

Approx. 16 hours to complete

English

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 3 of 4 in the

Data Analytics in the Public Sector with R Specialization

Intermediate Level

Approx. 16 hours to complete

English

Instructors

Christopher Brooks

Assistant Professor

School of Information

783,614 Learners

14 Courses

Paula Lantz

James B. Hudak Professor of Health Policy

Gerald R. Ford School of Public Policy

3,314 Learners

4 Courses

Offered by

University of Michigan

Syllabus - What you will learn from this course

Week1

Week 1

4 hours to complete

Week 1 | Policy Frameworks & Types of Policy Analysis

4 hours to complete

8 videos (Total 50 min), 4 readings, 2 quizzes

8 videos

Introduction to Course 3: Assisting Public Sector Decision Makers with Data and Policy Analysis1mWhat is Policy and Why it Matters7mPolicy Typology10mFacts About Public Policy2mPolicy Typology—Examples9mThe Policy Making Process5mPolicy Analysis: Definitions & Examples6mPolicy Analysis: Role of Data Analytics in the Policy Analysis7m

4 readings

Course Syllabus15mCourse Glossary of Terms10mHelp Us Learn About You10mWeek 1 Optional Readings & Resources10m

2 practice exercises

Policy Typology Knowledge Check20mWeek 1 Quiz: Policy Frameworks & Types of Policy Analysis30m

Week2

Week 2

4 hours to complete

Week 2 | Prospective Policy Analysis: What Should We Do?—Part 1

4 hours to complete

7 videos (Total 70 min)

7 videos

Framework for Policy Options Analysis—Part 13mFramework for Policy Options Analysis—Part 27mIntroduction to Inferential Statistical Analysis in R2mChi-squared Tests of Association13mt-Tests of Difference in Means12mANOVA Models12mp-Values & Simulation17m

3 practice exercises

Knowledge Check: Policy Options Analysis20mt-Tests of Difference in Means: Practice & Knowledge Check20mWeek 2 Quiz: EDA & Inferential Statistical Analysis in R2h

Week3

Week 3

3 hours to complete

Week 3 | Prospective Policy Analysis: What Should We Do?—Part 2

3 hours to complete

9 videos (Total 60 min), 1 reading, 2 quizzes

9 videos

Introduction to Policy Simulation Modeling5mExamples of Policy Simulation Models4mEconomic Analysis in Simulation Modeling: Cost-Benefit Analysis5mEconomic Analysis in Simulation Modeling: Cost-Effectiveness Analysis6mDealing with Uncertainty: Sensitivity Analysis6mExample of Sensitivity Analysis to Deal with Uncertainty5mPolicy Microsimulation: What is a Compartmental Model?7mA Basic Tobacco Control Compartment Model8mTobacco Control Compartmental Model: Menthol Cigarette Example10m

1 reading

Week 3 Optional Readings & Resources30m

2 practice exercises

Policy Microsimulation Modeling Knowledge Check20mWeek 3 Quiz: Policy Microsimulation Modeling 30m

Week4

Week 4

4 hours to complete

Week 4 | Program/Policy Evaluation: Did it Work?—Part 1

4 hours to complete

15 videos (Total 127 min), 2 readings, 4 quizzes

15 videos

What is Program Evaluation and Why it matters?9mTypes of Program Evaluation7mProgram Evaluation Framework9mFocusing the Design and Gathering Credible Evidence12mExample of a Research Design7mInternal and External Validity: the Basics8mInternal and External Validity: Examples8mCommon Research Designs for Evaluation In Public Sector12mExperimental Designs11mExamples of Randomized-Controlled Trials (RCTs) of Public Programs11mComing Up Next: The DC Garbage Can Case Study4mThe DC Garbage Can Intervention: Data Analysis7mThe DC Garbage Can Intervention: Joining Data5mThe DC Garbage Can Intervention: Wrap-Up8mOne More Thing For This Week: Random Assignment vs Random Selection2m

2 readings

Raise Taxes on Tobacco10mWeek 4 Optional Readings & Resources30m

4 practice exercises

Program Evaluation Knowledge Check20mResearch Design Knowledge Check20mThe DC Garbage Can Intervention: Practice & Knowledge Check20mWeek 4 Quiz: Program/Policy Evaluation30m

About the Data Analytics in the Public Sector with R Specialization

Every government entity collects and stores millions of data points to perform administrative and legislative duties, allocate resources, and make decisions. Professionals in the public sector need the necessary skills to accurately interpret and inform administrators and policymakers about the meaning behind these data.

This Specialization will equip you with fundamental technical skills using the R programming language to gather, manipulate, analyze, visualize, and interpret data to inform public policy and public administrative functions. Throughout four courses, you will gain new skills using the popular tidyverse packages, such as dplyr for data manipulation and ggplot for visualization. You will identify and address common political and ethical challenges in data analysis, and better understand public administration and public policy concepts using hands-on activities with real-world data sets. This course series is ideal for current or early-career professionals in the public sector looking to gain skills in analyzing public data effectively. There are no prerequisites, though programming experience, ideally with the R language, and basic applied statistics knowledge are recommended. The Google Data Analytics Professional Certificate offers such foundational skills. You will earn a dual badge when you complete the Google Career Certificate and this Specialization. All coursework is completed in RStudio in Coursera without the need to install additional software

Data Analytics in the Public Sector with R

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Assisting Public Sector Decision Makers With Policy Analysis

About this Course