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How can we make better graphs? An initiative to increase the graphical expertise and productivity of quantitative scientists
Author(s) -
Vandemeulebroecke Marc,
Baillie Mark,
Carr David,
Kanitra Linda,
Margolskee Alison,
Wright Andrew,
Magnusson Baldur
Publication year - 2018
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1912
Subject(s) - graphics , computer science , field (mathematics) , productivity , data science , computer graphics , core (optical fiber) , work (physics) , artificial intelligence , engineering , mathematics , computer graphics (images) , mechanical engineering , telecommunications , pure mathematics , economics , macroeconomics
Graphics are at the core of exploring and understanding data, communicating results and conclusions, and supporting decision-making. Increasing our graphical expertise can significantly strengthen our impact as professional statisticians and quantitative scientists. In this article, we present a concerted effort to improve the way we create graphics at Novartis. We provide our vision and guiding principles, before describing seven work packages in more detail. The actions, principles, and experiences laid out in this paper are applicable generally, also beyond drug development, which is our field of work. The purpose of this article is to share our experiences and help foster the use of good graphs in pharmaceutical statistics and beyond. A Graphics Principles "Cheat Sheet" is available online at https://graphicsprinciples.github.io/.