Hogg Award for For Excellence in Teaching Introductory Statistics. Mine is a Fellow of the ASA and Elected Member of the ISI as well as the winner of the 2021 Robert V. She is also the creator and maintainer of and she teaches the popular Statistics with R MOOC on Coursera. As part of this project she co-authored four open-source introductory statistics textbooks.
Mine works on the OpenIntro project, whose mission is to make educational products that are free, transparent, and lower barriers to education. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. This book helps you understand the theory that underpins ggplot2, and will help you create new types of graphics specifically tailored to your needs.Mine Çetinkaya-Rundel is Professor of the Practice at Duke University and Developer Educator at RStudio. Students 5,050 / Classrooms/Labs/Studios 102 / Programs 38. It describes the theoretical underpinnings of ggplot2 and shows you how all the pieces fit together. Sheridans Collaborative Online International Learning (COIL) projects where two or. If you’ve mastered the basics and want to learn more, read ggplot2: Elegant Graphics for Data Analysis. It provides a set of recipes to solve common graphics problems. If you want to dive into making common graphics as quickly as possible, I recommend The R Graphics Cookbook by Winston Chang.
If you’d like to follow a webinar, try Plotting Anything with ggplot2 by Thomas Lin Pedersen. If you’d like to take an online course, try Data Visualization in R With ggplot2 by Kara Woo. R for Data Science is designed to give you a comprehensive introduction to the tidyverse, and these two chapters will get you up to speed with the essentials of ggplot2 as quickly as possible.
The Data Visualisation and Graphics for communication chapters in R for Data Science. Currently, there are three good places to start: If you are new to ggplot2 you are better off starting with a systematic introduction, rather than trying to learn from reading individual documentation pages.
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