Physical Sciences and Mathematics Commons^™

Graphicacy For Numeracy: Review Of Fundamentals Of Data Visualization: A Primer On Making Informative And Compelling Figures By Claus O. Wilke (2019), Christy M. Bebeau

Numeracy

Wilke, Claus O. 2019. Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures. (Sebastopol, CA: O’Reilly Media, Inc.). 390 pp. ISBN 978-1-492-03108-6. First edition. First release: 03-15-2019.

Claus O. Wilke has authored an excellent reference about producing and understanding static figures, figures used online, in print, and for presentations. His book is neither a statistics nor programming text, but familiarity with basic statistical concepts is helpful. Written in three parts, the book presents both the math and artistic design aspects of telling a story through figures. Wilke makes extensive use of examples, labels them good, bad, …

Forewarned Is Forearmed: Review Of Curbing Catastrophe: Natural Hazards And Risk Reduction In The Modern World By Timothy H. Dixon (2017), Jason Makansi

Numeracy

Timothy H. Dixon. 2017. Curbing Catastrophe: Natural Hazards and Risk Reduction in the Modern World. (New York, NY: Cambridge University Press) 300 pp. ISBN 978-1108113663.

Curbing Catastrophe for the most part lives up to what is claimed in the foreword: “…a compelling account of recent and historical disasters, both natural and human-caused, drawing on common themes and providing a holistic understanding of hazards, disasters, and mitigation for anyone interested in this important and topical subject.” This is a pretty thorough treatment of an extraordinarily complex subject, and the gaps identified in this review should be considered explications more than …

Random Number Simulations Reveal How Random Noise Affects The Measurements And Graphical Portrayals Of Self-Assessed Competency, Edward Nuhfer, Christopher Cogan, Steven Fleisher, Eric Gaze, Karl Wirth

Numeracy

Self-assessment measures of competency are blends of an authentic self-assessment signal that researchers seek to measure and random disorder or "noise" that accompanies that signal. In this study, we use random number simulations to explore how random noise affects critical aspects of self-assessment investigations: reliability, correlation, critical sample size, and the graphical representations of self-assessment data. We show that graphical conventions common in the self-assessment literature introduce artifacts that invite misinterpretation. Troublesome conventions include: (y minus x) vs. (x) scatterplots; (y minus x) vs. (x) column graphs aggregated as quantiles; line …