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Matthew Renze

R is a popular open-source programming language for data analysis. In this course, you will learn how to create multivariate data visualizations with R in order to answer questions about your data.

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R is a popular open-source programming language for data analysis. In this course, you will learn how to create multivariate data visualizations with R in order to answer questions about your data.

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for creating a wide variety of data visualizations. In this course, Multivariate Data Visualization with R, you will learn how to answer questions about your data by creating multivariate data visualizations with R. First, you'll learn the basics about creating multivariate data visualizations with R, in order to have a strong foundation to build on. Next, you'll learn how to create and interpret data visualizations that involve various combinations of three categorical or numerical variables. Finally, you'll learn how to create and interpret data visualizations that involve an arbitrary number of variables at the same time. By the end of this course you'll have the skill required to create and interpret a variety of multivariate data visualizations using R.

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Syllabus

Course Overview
Introduction
Visualizing Three Categorical Variables
Visualizing Two Categorical and One Numeric Variables
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Visualizing One Categorical and Two Numeric Variables
Visualizing Three Numeric Variables
Visualizing Many Variables

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches multivariate data visualization, which is highly relevant to data analysis
Led by Matthew Renze, a leading instructor in data visualization
Builds a strong foundation for beginners in data visualization with R
Strengthens an existing foundation for intermediate learners in data visualization with R
Provides comprehensive study of one aspect of science, math, and technology
Taught by Matthew Renze, who is recognized for his work in data visualization

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Multivariate Data Visualization with R with these activities:
Review your knowledge of R basics
Ensure you have a strong foundation before starting the course.
Browse courses on R Programming
Show steps
  • Review your notes from previous R courses or tutorials.
  • Practice writing R code to perform basic tasks, such as data manipulation and visualization.
Read "Data Visualization with R" by Kieran Healy
Expand and reinforce your knowledge through additional reading.
Show steps
  • Read the book in its entirety.
  • Take notes on the key concepts.
  • Apply the concepts you learn to your own data visualization projects.
Follow tutorials on creating multivariate data visualizations with R
Gain additional support and guidance outside of class.
Show steps
  • Find tutorials that cover the topics you are interested in.
  • Follow the tutorials step-by-step.
  • Experiment with the code and data provided in the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice creating multivariate data visualizations with R
Strengthen the skills covered in class with more practice.
Show steps
  • Find a dataset that contains multiple variables.
  • Create a variety of data visualizations, including bar charts, line charts, and scatterplots.
  • Interpret the results of your data visualizations.
Attend a workshop on multivariate data visualization with R
Gain hands-on experience and learn from experts.
Show steps
  • Find a workshop that is relevant to your interests.
  • Register for the workshop.
  • Attend the workshop and participate in the activities.
Participate in a peer review session
Learn from your classmates and provide feedback.
Show steps
  • Find a peer who is also taking the course.
  • Agree on a time to meet and discuss the course material.
  • During the session, share your thoughts and ideas about the course material.
  • Provide feedback to your peer on their thoughts and ideas.
Create a blog post or article on multivariate data visualization with R
Solidify your understanding by teaching others.
Show steps
  • Choose a topic that you are interested in.
  • Research the topic thoroughly.
  • Write a blog post or article that is clear, concise, and engaging.
  • Share your blog post or article with others.
Participate in a data visualization competition
Test your skills and knowledge against others.
Show steps
  • Find a data visualization competition that you are interested in.
  • Read the competition rules and guidelines.
  • Create a data visualization that meets the competition requirements.
  • Submit your data visualization to the competition.

Career center

Learners who complete Multivariate Data Visualization with R will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts examine and interpret data, transforming it into actionable insights. To do this, they use a variety of techniques, including data mining, statistical analysis, and visualization, to understand and meet business needs. The course, Multivariate Data Visualization with R, is a perfect fit for aspiring Data Analysts. This course teaches learners how to create multivariate data visualizations with R, a valuable skill that allows for the effective analysis of data.
Marketing Analyst
Marketing Analysts use data to gain insights and help businesses make informed marketing decisions. They use various techniques to analyze data, including statistical analysis and data visualization. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Marketing Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand marketing data and make better decisions.
Data Scientist
Data Scientists are responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions. They use a variety of techniques, including statistical analysis, data mining, and machine learning. The course, Multivariate Data Visualization with R, is an excellent choice for aspiring Data Scientists. This course teaches learners how to create multivariate data visualizations with R, a valuable skill for Data Scientists to have.
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They use a variety of techniques, including data mining, statistical analysis, and data visualization. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Business Intelligence Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand business data and make better decisions.
Market Researcher
Market Researchers use data to understand consumer behavior and trends. They use a variety of techniques, including surveys, focus groups, and data analysis. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Market Researcher. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand market data and make better decisions.
Quantitative Analyst
Quantitative Analysts use data to help businesses make investment decisions. They use a variety of techniques, including statistical analysis, financial modeling, and data visualization. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Quantitative Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand financial data and make better decisions.
Operations Research Analyst
Operations Research Analysts use data to help organizations improve their operations. They use a variety of techniques, including mathematical modeling, simulation, and data analysis. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as an Operations Research Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand operational data and make better decisions.
Healthcare Analyst
Healthcare Analysts use data to help improve the quality and efficiency of healthcare. They use a variety of techniques, including statistical analysis, data mining, and data visualization. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Healthcare Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand healthcare data and make better decisions.
Financial Analyst
Financial Analysts use data to help businesses make investment decisions. They use a variety of techniques, including financial modeling, statistical analysis, and data visualization. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Financial Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand financial data and make better decisions.
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help businesses and organizations communicate complex information more effectively. They use a variety of techniques, including data visualization tools and software. The course, Multivariate Data Visualization with R, can be a great fit for those seeking a career as a Data Visualization Specialist. This course provides learners with the skills needed to create multivariate data visualizations that are both informative and visually appealing.
Consultant
Consultants provide advice and expertise to businesses and organizations. They use a variety of techniques, including data analysis, problem solving, and communication. The course, Multivariate Data Visualization with R, may be useful for those seeking a career as a Consultant. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand business data and make better decisions.
Product Manager
Product Managers are responsible for the development and success of products. They use a variety of techniques, including data analysis, market research, and customer feedback. The course, Multivariate Data Visualization with R, may be useful for those seeking a career as a Product Manager. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand product data and make better decisions.
User Experience (UX) Researcher
UX Researchers use data to understand how users interact with products and services. They use a variety of techniques, including user testing, surveys, and data analysis. The course, Multivariate Data Visualization with R, may be useful for those seeking a career as a UX Researcher. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand user data and make better decisions.
Business Analyst
Business Analysts use data to help businesses improve their operations and make better decisions. They use a variety of techniques, including data analysis, process improvement, and project management. The course, Multivariate Data Visualization with R, may be useful for those seeking a career as a Business Analyst. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand business data and make better decisions.
Software Engineer
Software Engineers design, develop, and maintain software applications. They use a variety of techniques, including programming, testing, and debugging. The course, Multivariate Data Visualization with R, may be useful for those seeking a career as a Software Engineer. This course provides learners with the skills needed to create multivariate data visualizations that can help them understand software data and make better decisions.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Multivariate Data Visualization with R.
Comprehensive guide to using ggplot2, a popular R package for creating elegant and informative data visualizations. It is highly recommended for learners who want to master ggplot2 and create stunning visuals.
Offers a comprehensive guide to using ggplot2 for data visualization in R. It is suitable for learners who want to develop proficiency in ggplot2 and create visually appealing and informative data visualizations.
Focuses on creating interactive web-based data visualizations using R, plotly, and shiny. It can be valuable for learners interested in exploring interactive data visualization techniques.
Provides a comprehensive overview of exploratory data analysis techniques using R. It valuable resource for learners who want to gain a deeper understanding of data analysis and visualization.
Provides a comprehensive overview of data science concepts and techniques, including data visualization. It is suitable for learners who want to gain a broader understanding of data science and its applications.
Provides a comprehensive overview of data science concepts and techniques, including data visualization. It is suitable for learners who want to gain a broader understanding of data science in a business context.
While this book covers advanced R programming topics, it also includes valuable insights into data visualization and statistical modeling techniques that can enhance the course material.
Covers advanced R programming topics, including data visualization. It is suitable for learners who want to extend their knowledge of R and enhance their data visualization skills.
Provides a solid foundation in data visualization principles and best practices. It valuable resource for learners who want to understand the concepts behind effective data visualization.
While this book focuses on data visualization using Python and JavaScript, it offers valuable insights into data visualization best practices and techniques that can be applied to R as well.

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