University of Michigan
Exploratory Data Analysis for the Public Sector with ggplot
University of Michigan

Exploratory Data Analysis for the Public Sector with ggplot

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

Taught in English

Some content may not be translated

Christopher Brooks
Paula Lantz

Instructors: Christopher Brooks

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Course

Gain insight into a topic and learn the fundamentals

Intermediate level
Some related experience required
18 hours (approximately)
Flexible schedule
Learn at your own pace

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

Details to know

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Assessments

13 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level
Some related experience required
18 hours (approximately)
Flexible schedule
Learn at your own pace

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Build your subject-matter expertise

This course is part of the Data Analytics in the Public Sector with R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

Welcome to the second course in the Data Analytics in the Public Sector with R—Exploratory Data Analysis for Public Administration with ggplot. This week, you will begin to develop the skills of exploratory data analysis through constructing ggplot plots and line plots in RStudio. You will also get to recognize the importance of data visualization for public administration and how powerful data visualization skills are in the profession of a data analyst.

What's included

9 videos6 readings4 quizzes1 app item1 discussion prompt1 ungraded lab

Welcome to Week 2! This week you will learn about the importance of Exploratory Data Analysis (EDA) for the core principle of equity. Building on the previous week, you will also continue to develop skills of exploratory data analysis through understanding frequencies and distributions and how to construct trendlines and histograms using RStudio.

What's included

9 videos3 readings5 quizzes1 app item

Welcome to Week 3! You will start this week exploring distributions and develop the skills of visualizing different distributions, such as boxplots, violin plots, and ridgeplots. You will also learn how to develop scale, coord, faceats across layers in ggplot, using RStudio.

What's included

5 videos2 quizzes

Welcome to Week 4, the last week in this course! This week you will learn the best practices for data visualization through communication principles and skills. You will also learn about information visualization theory and how to apply that in developing data visualization in RStudio.

What's included

12 videos3 readings2 quizzes1 app item2 discussion prompts1 plugin

Instructors

Christopher Brooks
14 Courses847,790 learners

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