|P.Mean >> Category >> Graphical display (created 2007-08-06).|
These links discuss some of the issues that you need to consider when displaying research data using a graph. Articles are arranged by date with the most recent entries at the top. You can find outside resources at the bottom of this page. Also see Descriptive statistics, Human side of statistics, Presenting research data, Writing research papers.
15. P.Mean: Whiskers in a boxplot (created 2012-07-27). Someone asked about how SPSS drew the "whiskers" in a boxplot. The length of the whiskers is supposed to be the distance from the 25th percentile to the minimum (75th percentile to the maximum) unless there are outliers. Outliers are defined as anything more than 1.5 box widths away from the end of either box.
14. What is a rug plot? (January/February 2012)
13. P.Mean: A very silly graph (created 2012-01-01). I know I shouldn't let this bother me, but I saw a graph today that was wrong on so many different levels. Let me explain.
13. What is a stem-and-leaf diagram? (January 2010)
12. What is a normal probability plot? (September/October 2009)
11. The Monthly Mean: Ban the bar! Pitch the pie! (September/October 2009)
10. What is a mosaic plot? (May/June 2009)
9. What is a boxplot? (January 2009)
8. P.Mean: Drawing simple mathematical graphs (created 2009-01-14). I'm looking for a good, basic, relatively easy-to-use graphing program, to draw simple mathematical graphs one would see in basic calculus, algebra, statistics. Something similar to Paint, but a step or two up from it, and that I could copy and paste images, venn diagrams, etc., into a Word file, and the quality would be publication quality. I want something that is MUCH more versatile than one would get using Excel or similar.
7. P.Mean: Venn diagrams with proportional areas (created 2008-09-23). I was asked by someone to come up with a graphic summary of a data set that includes three binary factors that can be either present or absent in any combination. Typically this can be illustrated with a Venn diagram, the intersection of three circles but I wondered if you could do a Venn diagram with areas proportion to the actual probabilities.
6. P.Mean: A misleading bar graph (created 2008-07-15). A regular contributor on EDSTAT-L, found an interesting bar graph on the DirecTV website.
The 10 Commandments for Figures. Keith Head, Sauder School of Business, University of British Columbia. Excerpt: If you need to satisfy me because I'm your prof or you think I might be a referee, then just follow the rules. If you want more information about the rationale behind the rules, they are mainly based on the books by Edward Tufte which are really worth reading for the examples and interesting discussion. This website was last verified on 2006-02-16. URL: www.pacific.commerce.ubc.ca/keith/figcoms.htm
2-D or not 2-D? (That is the question). Garr Reynolds. Excerpt: We can learn how to be better presenters by observing the masters. I often say, for example, that we can improve our presentations by emulating certain aspects of Steve Jobs' presentation style. Today, though, I'd like to talk about one aspect of Steve's presentation Tuesday that we can learn from by not emulating. And that is the use of 3-D charts to represent 2-D data. This website was last verified on 2006-02-21. URL: www.presentationzen.blogs.com/presentationzen/2006/01/2d_or_not_2d_th.html
Hans Rosling. 200 Countries, 200 Years, 4 Minutes - The Joy of Stats. 2010. More about this programme: http://www.bbc.co.uk/programmes/b00wgq0l Hans Rosling's famous lectures combine enormous quantities of public data with a sport's commentator's style to reveal the story of the world's past, present and future development. Now he explores stats in a way he has never done before - using augmented reality animation. In this spectacular section of 'The Joy of Stats' he tells the story of the world in 200 countries over 200 years using 120,000 numbers - in just four minutes. Plotting life expectancy against income for every country since 1810, Hans shows how the world we live in is radically different from the world most of us imagine. [Accessed December 2, 2010]. Available at: http://www.youtube.com/watch?v=jbkSRLYSojo&feature=youtube_gdata_player
Yu H, Agarwal S, Johnston M, Cohen A. Are figure legends sufficient? Evaluating the contribution of associated text to biomedical figure comprehension. Journal of Biomedical Discovery and Collaboration. 2009;4(1):1. Available at: http://www.j-biomed-discovery.com/content/4/1/1 [Accessed February 23, 2009].
Chart Burn: The "mountain charts" in fund ads can be confusing. Jason Zweig. Money 2000: 67-69.. Description: to be added soon.
Data Visualization: Modern Approaches. Vitaly Friedman and Sven Lennartz. Published August 2, 2007 in Smashing Magazine. Description: This website offers some innovative ways of displaying data, especially unusual data sets. URL: www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/
Depicting Error. Howard Wainer. The American Statistician 1996: 50(2); 101-111. Description: to be added soon.
Julie Rehmeyer. Florence Nightingale: The Passionate Statistician - Science News. Science News. 2008. Excerpt: "When Florence Nightingale arrived at a British hospital in Turkey during the Crimean War, she found a nightmare of misery and chaos. Men lay crowded next to each other in endless corridors. The air reeked from the cesspool that lay just beneath the hospital floor. There was little food and fewer basic supplies. By the time Nightingale left Turkey after the war ended in July 1856, the hospitals were well-run and efficient, with mortality rates no greater than civilian hospitals in England, and Nightingale had earned a reputation as an icon of Victorian women. Her later and less well-known work, however, saved far more lives. She brought about fundamental change in the British military medical system, preventing any such future calamities. To do it, she pioneered a brand-new method for bringing about social change: applied statistics." [Accessed February 23, 2010]. Available at: http://www.sciencenews.org/view/generic/id/38937/title/Math_Trek__Florence_Nightingale_The_passionate_statistician.
How to interpret figures in reports of clinical trials. Stuart J. Pocock, Thomas G. Travison, Lisa M. Wruck. BMJ 2008: 336(7654); 1166-1169. [Full text] [PDF]. Description: This article reviews several commonly used data display methods and explains what a non-technical reader should look for. [[Note that full text and PDF are not available to the general public until December 2008]]
Webpage: Ben Greenman. I Love Charts – Ben Greenman's Museum of Silly Charts Excerpt: "My interest in charts springs primarily from my disinterest in charts. Reality is so messy. Nothing that passes for a fact ever really is one. When I was a kid, infographics were intoxicating because they promised a world of order, and it's specifically this promise that has come, over time, to seem like a cruel deception. You'll never really get an elegant presentation of so-called facts that accurately and meaningfully represents reality. So, as much as I'm drawn to those charts, I'm also drawn to charts that obfuscate, or thwart, or somehow sharpen our sense of the absurdity of trying to accurately present and analyze information." [Accessed on May 11, 2011]. http://ilovecharts.tumblr.com/BenGreenman.
Lightness Perception and Lightness Illusions. Edward H. Adelson. Accessed on 2003-10-13. Excerpt: "Sometimes people think of illusions as failures of the visual system. However, they are usually caused by useful mechanisms that have been forced into an odd situation by a specially constructed stimulus. Without the underlying mechanisms, visual perception would not be possible. In normal life, the mechanisms work so smoothly that they are completely hidden. Through the use of illusions, we can reveal their action, and thereby study how normal vision works." www-bcs.mit.edu/gaz/
Anonymous. Statistical Graphics and more. Excerpt: "Statistical Graphics, Data Visualization, Visual Analytics, Data Analysis, Data Mining, User Interfaces - you name it" [Accessed February 5, 2010]. Available at: http://www.theusrus.de/blog/.
Harrell FE. Statistical Graphics Course. Available at: http://biostat.mc.vanderbilt.edu/wiki/Main/StatGraphCourse [Accessed August 18, 2009]. Excerpt: Graphical methods are being increasingly used for exploratory data analysis. Some of the many graphical tools that are useful in this setting are scatterplot matrices, nonparametric smoothers, and tree diagrams. Statistical graphics for presenting information have been used much longer, but most of the commonly used graphics used in papers, presentations, and the popular media, such as bar charts and pie charts, are either poor or misleading in communicating information to the reader. This short course begins with a series of graphical horror stories from the scientific and lay press. Then elements of graphical perception and good graph construction, many from the writings of Bill Cleveland, are covered. Practical suggestions for choosing the best chart or graph type, making good and clear graphics, and formatting are covered. Techniques for simultaneous presentation of multiple variables are described.
Statistical graphics: mapping the pathways of science. H. Wainer, P. F. Velleman. Annu Rev Psychol 2001: 52305-35. [Medline]. Description: to be added soon.
Lazic S, Mason S, Michell A, Barker R. Visualising disease progression on multiple variables with vector plots and path plots. BMC Medical Research Methodology. 2009;9(1):32. Available at: http://www.biomedcentral.com/1471-2288/9/32 [Accessed May 29, 2009]. Description: This paper shows how to use vector plots to display longitudinal changes in individual patients.
All of the material above this paragraph is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2017-06-15. The material below this paragraph links to my old website, StATS. Although I wrote all of the material listed below, my ex-employer, Children's Mercy Hospital, has claimed copyright ownership of this material. The brief excerpts shown here are included under the fair use provisions of U.S. Copyright laws.
5. Stats: Stair step interpolation in R (November 15, 2007). I am working on some charts that show discrete (sudden) jumps at specific time points. This requires the use of stair step interpolation, because if you just connected the lines, it would imply a linear transition between consecutive points.
4. Stats: Patterns to look for in a histogram (September 21, 2007). When you plot your data in a histogram (or a stem and leaf diagram), you should look for patterns. Here are examples of three of the most important ones.
3. Stats: Colors for R graphs (June 28, 2006). I tend to use color sparingly in graphs because most of my graphs end up in black and white in the final production. Even on my web pages, which appear in color, I try to avoid too much use of color because I often print these pages on a black and white printer.
2. Stats: Graphics options in R (September 12, 2006). When you are producing graphics in R, the default option does not save your graphs for later review. You can change this in several ways. My comments will discuss the options for R running under Microsoft Windows. There are similar approaches that work for other systems.
1. Stats: Pitch the pie! Ban the bar! (June 5, 2003). This is an outline of a speech that I gave to Bluejacket Toastmasters on June 5, 2003. I work a lot with numbers and I've found that there is usually a good way to display those numbers and a bad way. Here's an example. It's a pie chart with bright bold colors and a deep 3-D effect. Is this a good way to display the data? WRONG! You should pitch the pie. Here's another example. It's a bar chart with big bold purple bars. Is this a good way to display the data? WRONG AGAIN! You should ban the bar.
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This work is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2017-06-15.