remotes::install_github('jbryer/VisualStats')Visual Statistics
Last updated on November 06, 2024
1 Introduction
This website is largely inspired by what our advisor, colleague, and friend Bob Pruzek called elemental graphics. The first two paragraphs from Pruzek and Helmreich (2010) succinctly introduces the core ideas of elemental graphics:
To be most informative in practice, statistical methods should help users see relationships, hypothesized or discovered, among sets of variates or between groups with respect to one or more variates. Particular methods are usually defined using specific models, or by relational questions. Some procedures pose explicit questions that can be approached both descriptively and through inference…
An elemental graphic facilitates direct visualization of data in a way that illuminates the questions that a particular statistical method seeks to answer. For example, a simple scatterplot may be considered the canonical example of an elemental graphic for the association of two variables, and by incorporating superposition of a regression line, especially if augmented with vertical lines (from the points to the regression line) that show “errors”, such a plot can become an elemental graphic for a linear prediction.
Their initial paper focused on a specific graphic for analysis of variance (ANOVA), which we cover with some additions. The chapters of this book attempt to take that same philosophy that there are natural graphics that exemplify important statistical concepts beyond ANOVA. This book is not intended to be a standalone introductory statistics book but instead a collection of articles we have used to support the teaching of statistics.
This is an online book because we have found that by having students interact with the graphics, often by controlling specific parameters and/or adding features one-by-one provides a deeper understanding of the concepts. The introduction of the Shiny (Chang et al. 2023) R package has greatly simplified the process of creating interactive visualiztions.
All of the Shiny applications, supporting functions, and data sets are included in the VisualStats R package. This can be downloaded using the following command:
This website/book does not intend to be another introductory statistics book, there are plenty of fantastic options available, but instead a collection of Shiny applications and chapters to support those visualizations. Our philosophy is that students can better understand the statistical formulas instrumental to the field itself through geometric representations. Take for example the fact that many statistical formulas square terms. Drawing a square for these formulas becomeas a natural way of exploring the features of what that statistical formula is attempting to solve.
1.1 Contributions
This website is a work in progress. If you have suggestions and/or edits you can either open an issue on Github or click “edit this page” at the bottom of each page.
1.2 Colophon
This book was creating using Quarto (Allaire and Dervieux 2024) and hosted on Github. The interactive components were created using Shiny (Chang et al. 2023). All of the figures were created using the grammar of graphics (Wilkinson 2005) framework as implemented by the ggplot2 package (Wickham 2016).
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