Effective Visual Communication for the Quantitative Scientist

Effective visual communication is a core competency for pharmacometricians, statisticians, and, more generally, any quantitative scientist. It is essential in every step of a quantitative workflow, from scoping to execution and communicating results and conclusions. With this competency, we can bett...

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Main Authors: Marc Vandemeulebroecke, Mark Baillie, Alison Margolskee, Baldur Magnusson
Format: Article
Language:English
Published: Wiley 2019-10-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12455
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spelling doaj-65b32a1bb42b4759aa0d1be9d15b8cf22020-11-25T03:50:14ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062019-10-0181070571910.1002/psp4.12455Effective Visual Communication for the Quantitative ScientistMarc Vandemeulebroecke0Mark Baillie1Alison Margolskee2Baldur Magnusson3Biostatistical Sciences and Pharmacometrics Novartis Pharma AG Basel SwitzerlandBiostatistical Sciences and Pharmacometrics Novartis Pharma AG Basel SwitzerlandBiostatistical Sciences and Pharmacometrics Novartis Institutes for Biomedical Research Cambridge Massachusetts USABiostatistical Sciences and Pharmacometrics Novartis Pharma AG Basel SwitzerlandEffective visual communication is a core competency for pharmacometricians, statisticians, and, more generally, any quantitative scientist. It is essential in every step of a quantitative workflow, from scoping to execution and communicating results and conclusions. With this competency, we can better understand data and influence decisions toward appropriate actions. Without it, we can fool ourselves and others and pave the way to wrong conclusions and actions. The goal of this tutorial is to convey this competency. We posit three laws of effective visual communication for the quantitative scientist: have a clear purpose, show the data clearly, and make the message obvious. A concise “Cheat Sheet,” available on https://graphicsprinciples.github.io, distills more granular recommendations for everyday practical use. Finally, these laws and recommendations are illustrated in four case studies.https://doi.org/10.1002/psp4.12455
collection DOAJ
language English
format Article
sources DOAJ
author Marc Vandemeulebroecke
Mark Baillie
Alison Margolskee
Baldur Magnusson
spellingShingle Marc Vandemeulebroecke
Mark Baillie
Alison Margolskee
Baldur Magnusson
Effective Visual Communication for the Quantitative Scientist
CPT: Pharmacometrics & Systems Pharmacology
author_facet Marc Vandemeulebroecke
Mark Baillie
Alison Margolskee
Baldur Magnusson
author_sort Marc Vandemeulebroecke
title Effective Visual Communication for the Quantitative Scientist
title_short Effective Visual Communication for the Quantitative Scientist
title_full Effective Visual Communication for the Quantitative Scientist
title_fullStr Effective Visual Communication for the Quantitative Scientist
title_full_unstemmed Effective Visual Communication for the Quantitative Scientist
title_sort effective visual communication for the quantitative scientist
publisher Wiley
series CPT: Pharmacometrics & Systems Pharmacology
issn 2163-8306
publishDate 2019-10-01
description Effective visual communication is a core competency for pharmacometricians, statisticians, and, more generally, any quantitative scientist. It is essential in every step of a quantitative workflow, from scoping to execution and communicating results and conclusions. With this competency, we can better understand data and influence decisions toward appropriate actions. Without it, we can fool ourselves and others and pave the way to wrong conclusions and actions. The goal of this tutorial is to convey this competency. We posit three laws of effective visual communication for the quantitative scientist: have a clear purpose, show the data clearly, and make the message obvious. A concise “Cheat Sheet,” available on https://graphicsprinciples.github.io, distills more granular recommendations for everyday practical use. Finally, these laws and recommendations are illustrated in four case studies.
url https://doi.org/10.1002/psp4.12455
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