- Email: [email protected]
The Medium Is the Message: Thoughts on Picture Perfect Presentation
The Journal of Foot & Ankle Surgery 52 (2013) 415–416
Contents lists available at ScienceDirect
The Journal of Foot & Ankle Surgery journal homepage: www.jfas.org
Investigators’ Corner
The Medium Is the Message: Thoughts on Picture Perfect Presentation Daniel C. Jupiter, PhD Assistant Professor of Surgery, Department of Surgery, Texas A & M Health Science Center, College of Medicine; Research Scientist I, Scott and White Memorial Clinic and Hospital; and Research Assistant, Central Texas VA Health Care System, Temple, TX
a r t i c l e i n f o
a b s t r a c t
Keywords: small multiples Tufte
Clear presentation of results leads to easier interpretation and appreciation by readers. Opinions and tips are offered to ease clear communication. Ó 2013 by the American College of Foot and Ankle Surgeons. All rights reserved.
We all have had the frustrating experience of reading poorly written, unclear articles. But, in fairness, many of us also have had the frustrating experience of trying to write well and with clarity. I’m departing, in this Investigators’ Corner, from talking about facts (statistics) to giving my personal opinions (on presentation of results). The expectation is not that the reader will take my suggestions or opinions as set in stone; rather, the hope is that the ideas here will offer a starting point for thinking about better presentation. Doubtless, some of what I say will be glaringly obvious, but as noted in the Purloined Letter, we often don’t see the obvious precisely because it’s in plain sight. I often think about analyses and, in fact, entire articles, as falling into 3 categories:
Financial Disclosure: None reported. Conflict of Interest: None reported. Address correspondence to: Daniel C. Jupiter, PhD, 2401 South 31st Street, Temple, TX 76508. E-mail address: [email protected]
1. Descriptive: This category looks at a population. Who does the population encompass and what does the population look like? How many men? How many women? Are there diabetics? Is the sample similar to the patients that we see in our local clinics? 2. Exploratory: This is an extension of the descriptive category. I am looking for clues; therefore, I run a test or tests. For example, I not only look at the population of interest but also run statistical tests to see if, perhaps, there is an age difference between those with and without diabetes. I may not have a hypothesis in mind, but I simply run a test. Exploratory analyses can be more complex as well, and they may involve multivariate regression. 3. Hypothesis testing: This is the style of scientific article we are accustomed to reading. For example, I hypothesize that those who smoke will be more likely to have cancer (or perhaps that those with cancer are more likely to have smoked), and I test that hypothesis. Hypotheses can be about superiority, noninferiority, equivalence, and so on. These are not, of course, cut and dry categorizations, but they help me organize my thoughts both about analyses that I am planning or running and about analyses that I am reading.
1067-2516/$ - see front matter Ó 2013 by the American College of Foot and Ankle Surgeons. All rights reserved. http://dx.doi.org/10.1053/j.jfas.2012.12.001
416
D.C. Jupiter / The Journal of Foot & Ankle Surgery 52 (2013) 415–416
Even within a single article that I am writing, especially a hypothesis-testing type, I find that it helps if I divide my presentation into 3 tasks: 1. Describe the population I am studying in terms of both the demographics and the covariates and outcomes related to the question of interest. 2. Present the statistical tests used to establish the associations of interest under my hypothesis. 3. Explore the data further, often using more complex analyses, to clarify what I have seen or to generate novel ideas. I find that breaking the presentation into these distinct parts, even if the interstices are blurry, helps enormously. I tend to think about my graphic displays in a similar fashion: each table or graph pertains to 1 and only 1 of the 3 tasks just listed. My goal is to guide readers by helping them make the same distinctions between parts of an analysis while reading that I made while writing. Thus, a table for demographics, a table for main results of the central analysis, and tables for results of exploratory analyses make reading easier. Although graphs can make compelling arguments and they certainly are easier on the eye than tables, they often are not as data rich. My thinking along these lines is greatly influenced by the work of Edward Tufte (1–4), whose beautiful books provide plentiful examples of graphics done well and of graphics gone terribly wrong. Per Tufte, the ratio of information to ink should be high: a bar chart comparing 2 groups or a pie graph describing basic components of a population are wasteful of both ink and space. Further, a chart cannot as accurately or as densely convey information as a table does. The human eye is trained to interpret dense data. We easily find the Montreal Canadiens’ score and standings on the sports pages or the stock price of IBM on the stock pages, all within a sea of numbers! Additionally, graphs are easily manipulated
regarding scale. A difference of 1% can be made to look either large or small, depending on scale. It is much more difficult to manipulate a table in this way. Tables should highlight the data, not the grid. Preferably, grid lines are light gray so as not to distract the reader’s attention from the content of the cells (these are not prison cells capturing our data, after all). A similar caveat applies to graphs, in which the information, not the supporting structures on which the information hangs (such as axes), should be highlighted. Also in the vein of not distracting the effects that can arise from reader, be careful of things such as moire injudicious use of crosshatching. One way in which graphics are appropriately and effectively used (and there are many others) is to express what Tufte calls small multiples: a collection of similar graphs grouped for easy comparison. An example is the delightful history of avant-garde art by Marco Marilungo (5) or maps from the Centers for Disease Control and Prevention showing the development of the obesity epidemic in the United States (6,7). These are not definite prescriptions! There are exceptions to any of rules that I (and others) have proposed, but these are guidelines to consider when planning presentation of work. References 1. Tufte E. Visual Display of Quantitative Information, Graphics Press, Cheshire, CT, 1983. 2. Tufte E. Envisioning Information, Graphics Press, Cheshire, CT, 1990. 3. Tufte E. Visual Explanations: Images and Quantities, Evidence and Narrative, Graphics Press, Cheshire, CT, 1997. 4. Tufte E. Beautiful Evidence, Graphics Press, Cheshire, CT, 2006. 5. Marilungo M. Postcards of the artistic avant-garde. Available at: http://www. marilungo.com/eng/marco-marilungo-pictor-avant-garde-cards.html. Accessed October 2, 2012. 6. Centers for Disease Control and Prevention. Overweight and Obesity. Available at: http://www.cdc.gov/obesity/data/adult.html. Accessed November 30, 2012. 7. Positive Choice Wellness Center. Available at http://www.positivechoice.org/ wellness-blog/never-underestimate-the-power-of-a-few-small-choices. Accessed December 5, 2012.
Contents lists available at ScienceDirect
The Journal of Foot & Ankle Surgery journal homepage: www.jfas.org
Investigators’ Corner
The Medium Is the Message: Thoughts on Picture Perfect Presentation Daniel C. Jupiter, PhD Assistant Professor of Surgery, Department of Surgery, Texas A & M Health Science Center, College of Medicine; Research Scientist I, Scott and White Memorial Clinic and Hospital; and Research Assistant, Central Texas VA Health Care System, Temple, TX
a r t i c l e i n f o
a b s t r a c t
Keywords: small multiples Tufte
Clear presentation of results leads to easier interpretation and appreciation by readers. Opinions and tips are offered to ease clear communication. Ó 2013 by the American College of Foot and Ankle Surgeons. All rights reserved.
We all have had the frustrating experience of reading poorly written, unclear articles. But, in fairness, many of us also have had the frustrating experience of trying to write well and with clarity. I’m departing, in this Investigators’ Corner, from talking about facts (statistics) to giving my personal opinions (on presentation of results). The expectation is not that the reader will take my suggestions or opinions as set in stone; rather, the hope is that the ideas here will offer a starting point for thinking about better presentation. Doubtless, some of what I say will be glaringly obvious, but as noted in the Purloined Letter, we often don’t see the obvious precisely because it’s in plain sight. I often think about analyses and, in fact, entire articles, as falling into 3 categories:
Financial Disclosure: None reported. Conflict of Interest: None reported. Address correspondence to: Daniel C. Jupiter, PhD, 2401 South 31st Street, Temple, TX 76508. E-mail address: [email protected]
1. Descriptive: This category looks at a population. Who does the population encompass and what does the population look like? How many men? How many women? Are there diabetics? Is the sample similar to the patients that we see in our local clinics? 2. Exploratory: This is an extension of the descriptive category. I am looking for clues; therefore, I run a test or tests. For example, I not only look at the population of interest but also run statistical tests to see if, perhaps, there is an age difference between those with and without diabetes. I may not have a hypothesis in mind, but I simply run a test. Exploratory analyses can be more complex as well, and they may involve multivariate regression. 3. Hypothesis testing: This is the style of scientific article we are accustomed to reading. For example, I hypothesize that those who smoke will be more likely to have cancer (or perhaps that those with cancer are more likely to have smoked), and I test that hypothesis. Hypotheses can be about superiority, noninferiority, equivalence, and so on. These are not, of course, cut and dry categorizations, but they help me organize my thoughts both about analyses that I am planning or running and about analyses that I am reading.
1067-2516/$ - see front matter Ó 2013 by the American College of Foot and Ankle Surgeons. All rights reserved. http://dx.doi.org/10.1053/j.jfas.2012.12.001
416
D.C. Jupiter / The Journal of Foot & Ankle Surgery 52 (2013) 415–416
Even within a single article that I am writing, especially a hypothesis-testing type, I find that it helps if I divide my presentation into 3 tasks: 1. Describe the population I am studying in terms of both the demographics and the covariates and outcomes related to the question of interest. 2. Present the statistical tests used to establish the associations of interest under my hypothesis. 3. Explore the data further, often using more complex analyses, to clarify what I have seen or to generate novel ideas. I find that breaking the presentation into these distinct parts, even if the interstices are blurry, helps enormously. I tend to think about my graphic displays in a similar fashion: each table or graph pertains to 1 and only 1 of the 3 tasks just listed. My goal is to guide readers by helping them make the same distinctions between parts of an analysis while reading that I made while writing. Thus, a table for demographics, a table for main results of the central analysis, and tables for results of exploratory analyses make reading easier. Although graphs can make compelling arguments and they certainly are easier on the eye than tables, they often are not as data rich. My thinking along these lines is greatly influenced by the work of Edward Tufte (1–4), whose beautiful books provide plentiful examples of graphics done well and of graphics gone terribly wrong. Per Tufte, the ratio of information to ink should be high: a bar chart comparing 2 groups or a pie graph describing basic components of a population are wasteful of both ink and space. Further, a chart cannot as accurately or as densely convey information as a table does. The human eye is trained to interpret dense data. We easily find the Montreal Canadiens’ score and standings on the sports pages or the stock price of IBM on the stock pages, all within a sea of numbers! Additionally, graphs are easily manipulated
regarding scale. A difference of 1% can be made to look either large or small, depending on scale. It is much more difficult to manipulate a table in this way. Tables should highlight the data, not the grid. Preferably, grid lines are light gray so as not to distract the reader’s attention from the content of the cells (these are not prison cells capturing our data, after all). A similar caveat applies to graphs, in which the information, not the supporting structures on which the information hangs (such as axes), should be highlighted. Also in the vein of not distracting the effects that can arise from reader, be careful of things such as moire injudicious use of crosshatching. One way in which graphics are appropriately and effectively used (and there are many others) is to express what Tufte calls small multiples: a collection of similar graphs grouped for easy comparison. An example is the delightful history of avant-garde art by Marco Marilungo (5) or maps from the Centers for Disease Control and Prevention showing the development of the obesity epidemic in the United States (6,7). These are not definite prescriptions! There are exceptions to any of rules that I (and others) have proposed, but these are guidelines to consider when planning presentation of work. References 1. Tufte E. Visual Display of Quantitative Information, Graphics Press, Cheshire, CT, 1983. 2. Tufte E. Envisioning Information, Graphics Press, Cheshire, CT, 1990. 3. Tufte E. Visual Explanations: Images and Quantities, Evidence and Narrative, Graphics Press, Cheshire, CT, 1997. 4. Tufte E. Beautiful Evidence, Graphics Press, Cheshire, CT, 2006. 5. Marilungo M. Postcards of the artistic avant-garde. Available at: http://www. marilungo.com/eng/marco-marilungo-pictor-avant-garde-cards.html. Accessed October 2, 2012. 6. Centers for Disease Control and Prevention. Overweight and Obesity. Available at: http://www.cdc.gov/obesity/data/adult.html. Accessed November 30, 2012. 7. Positive Choice Wellness Center. Available at http://www.positivechoice.org/ wellness-blog/never-underestimate-the-power-of-a-few-small-choices. Accessed December 5, 2012.