Associate Professor of Information
Exploratory Data Analysis for the Public Sector with ggplot
What You'll Learn
- Understand the core pillars of the public sector and the core functions of public administration through statistical Exploratory Data Analysis (EDA)
- Use R to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting
4 Modules
16 Hours
4 hrs per module (approx.)
Rating
About Exploratory Data Analysis for the Public Sector with ggplot
Learn about the core pillars of the public sector and the core functions of public administration through statistical Exploratory Data Analysis (EDA). Learn analytical and technical skills using the R programming language to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Technical skills in this course will focus on the ggplot2 library of the tidyverse, and include developing bar, line, and scatter charts, generating trend lines, and understanding histograms, kernel density estimations, violin plots, and ridgeplots. These skills are enhanced with lessons on best practices for good information visualization design. Upon completing this course, you will understand the layered grammar of graphics and its implementation in ggplot2, all while exploring a diverse set of authentic public datasets.
All coursework is completed in RStudio in Coursera without the need to install additional software.
This is the second 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
- Data Visualization
- Ggplot2
- Public Administration
- Statistical Graphics
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Welcome to Exploratory Data Analysis for the Public Sector with ggplot, an online course that introduces data analytics skills for public administration and policy. Learners will engage in both understanding public administration/policy concepts and hands-on application activities applicable to administration/policy. The course is part of the Data Analytics in the Public Sector with R series.
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: Introduction to Visualization with ggplot2
- Video: Introduction to Course 2: Exploratory Data Analysis with ggplot2
- Reading: Course Syllabus
- Reading: Course Glossary of Terms
- Discussion Prompt: Meet Your Fellow Learners
- Reading: Help Us Learn About You
- Ungraded Lab: RStudio
- Video: A Layered Grammar of Graphics
- Video: Factors in R
- Graded Assignment: Factors in R: Practice & Knowledge Check
- Video: Our First ggplot Plot
- Video: Our First ggplot Plot: A little more Aesthetic
- Graded Assignment: Drawing a with ggplot in R: Practice & Knowledge Check
- Video: Exploring ggplot
- Video: Line Plots
- Graded Assignment: Exploring ggplot in R: Practice & Knowledge Check
- Video: The Power of Data Visualization for Public Administration
- Reading: Week 1 Assignment: Data Visualization in R with ggplot2
- Reading: R Code Solution for Week 1 Assignment: Data Visualization in R with ggplot2
- Reading: Week 1 Optional Readings & Resources
- Video: One More Thing for this Week: Case Study of EDA of a Disturbing Trend
Module 2: Fundamentals of Exploratory Data Analysis (EDA)
- Video: Equity as a Core Principle of Public Administration
- Video: Example: Digital Equity
- Video: The Importance of Equity in Public Health: Interview with Dr. Joneigh Khaldun
- Graded Assignment: EDA & Equity Knowledge Check
- Video: Trendlines: the Basics
- Video: Trendlines: Understanding Trends & Going Further with Them
- Graded Assignment: Trendlines in R: Practice & Knowledge Check
- Video: Distributions and Histograms: Getting Started
- Video: A Deep Dive into Histograms
- Graded Assignment: Histograms in R: Practice & Knowledge Check
- Video: Making a Population Pyramid: The Base
- Video: Improving the Visuals of a Population Pyramid
- Graded Assignment: Population Pyramids in R: Practice & Knowledge Check
- Reading: Week 2 Assignment: Fundamentals of Exploratory Data Analysis
- Reading: R Code Solution for Week 2 Assignment
- Reading: Week 2 Optional Readings & Resources
Module 3: Visualizing Populations and Trends with R
- Video: Let's go Fishing!
- Video: Boxplots
- Video: Boxplots: Increasing Variables
- Graded Assignment: Boxplots in R: Practice & Knowledge Check
- Video: Violin Plots
- Video: Ridgeplots
- Graded Assignment: Violin & Ridgeplots in R: Practice & Knowledge Check
Module 4: Best Practices for Data Visualization
- Video: Beware: Misleading Data Visualization
- Ungraded Plugin: How Coronavirus Charts can Mislead Us?
- Video: Communication Principles for Data Analysts
- Discussion Prompt: Share the Worst Data Visualization you Came Across
- Video: Introduction to Design of Visual Information
- Video: Graphical heuristics: Data-ink ratio (Edward Tufte)
- Video: Graphical heuristics: Chart junk (Edward Tufte)
- Video: Graphical heuristics: Lie Factor and Spark Lines (Edward Tufte)
- Video: The Truthful Art (Alberto Cairo)
- Discussion Prompt: Must a visual be enlightening?
- Video: Tools for Thinking about Design
- Video: Small Multiples
- Video: SPLOMs
- Graded Assignment: Small Multiples in R: Practice & Knowledge Check
- Reading: Week 4 Assignment: Best Practices for Data Visualization
- Reading: Week 4 Optional Readings & Resources
- Video: One More Thing for This Week!: World Data Visualization Prize in 2019
- Video: Congratulations on Completing the Course!
- Reading: Course Survey
Grading Policy
The course grade is based on six quizzes and assignments that equal 100% of the final grade.
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
