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Presenting Data Effectively: Communicating Your Findings for Maximum Impact
Make an impact with your research data! Focusing on the guiding principles of presenting data in evidence-based ways so that audiences are effectively engaged and researchers are better understood, Presenting Data Effectively offers the best communication strategies available to those working with data. With this accessible step-by-step guide, anyone―from students developing a research poster for a school project to faculty and researchers presenting data at a conference―can learn how to present and communicate their research findings in more interesting and effective ways. Author Stephanie Evergreen draws on her extensive experience in the study of research reporting, interdisciplinary evaluation, and data visualization, as well as from diverse interdisciplinary fields, including cognitive psychology, communications, and graphic design, to extract tangible and practical data-reporting communication lessons and insights. She then demonstrates how to apply those principles to the design of data presentations to make it easier for the audience to understand, remember, and use the data.
200 pages, Paperback
First published October 1, 2013
34 people are currently reading
530 people want to read
About the author
Stephanie D.H. Evergreen
10 books25 followersDr. Stephanie Evergreen is an internationally-recognized speaker, designer, and researcher. She is best known for bringing a research-based approach to helping researcher better communicate their work through more effective graphs, slides, and reports. She holds a PhD in interdisciplinary research, which included a dissertation on the extent of graphic design use in written research reporting. Dr. Evergreen has trained researchers worldwide through keynote presentations and workshops, for clients including Time, Verizon, Head Start, American Institutes for Research, Rockefeller Foundation, Brookings Institute, and the United Nations. She is the 2015 recipient of the American Evaluation Association’s Guttentag award, given for notable accomplishments early in a career. She writes a popular blog on data presentation at StephanieEvergreen.com. Her first book, Presenting Data Effectively: Communicating Your Findings for Maximum Impact, was published by Sage in Fall 2013. Her second book, Effective Data Visualization, was published in Spring 2016. Both books hit #1 on Amazon bestseller lists. Presenting Data Effectively is now in its second edition.
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Displaying 1 - 20 of 20 reviews
November 8, 2018
I got a copy of Presenting Data Effectively to see if it might be helpful in any of my undergrad or master's classes. I'm mostly interested in better-looking Powerpoints; reports and other documents aren't so urgent for what I teach right now. The book is a very helpful primer in basic issues of visual design. I don't know that I'll use the whole book verbatim in any class, but I will use chapters from it, or at least knowledge and tips I gained from it.
For me, the most interesting chapters were the ones about typefaces and colors. In addition to the helpful, entry-level information, Stephanie Evergreen has also included links to some great websites that I wasn't familiar with.
Less interesting to me was the chapter called "Arrangement," which seemed like the "Miscellaneous" box when I'm moving. And that's really one of the book's primary difficulties. If it were only about Powerpoint design, that would be focused and great, or only about report documents, or only about graphs and charts. But Evergreen covers a little of this and a little of that, and so it feels just a little scattered.
My other criticism of the book is Evergreen's tone. I've never seen a textbook where the author is so obsessed with herself, using a very informal, almost flippant, writing style. I don't mind if a textbook isn't as cold and sterile as the standard once required, but my goodness, reading this book often feels like listening to the caffeine-hyped monologue of a college student. I don't need a textbook to tell me I'm a "Rock Star"; I just want information, clearly presented. If this were a normal book in the $20 range, all of this would be fine, and Evergreen could do what she wants. But since it's classified as "textbook," students are paying quite a lot for it—currently $52.13 on Amazon.com. And with that price, I expect a tone that is more respectful toward the reader. I recommend that Sage assign Evergreen a co-author in future editions, to try to temper the voice in the book.
A good thing about the textbook is that the $52.13 gets you full-color pages, which is completely necessary for this topic. I can't believe the first edition of this book wasn't in color! It's a real gift to be able to enjoy the accompanying illustrations to the fullest.
Criticisms aside, Presenting Data Effectively was very helpful for me, and I recommend it to teachers at any level.
For me, the most interesting chapters were the ones about typefaces and colors. In addition to the helpful, entry-level information, Stephanie Evergreen has also included links to some great websites that I wasn't familiar with.
Less interesting to me was the chapter called "Arrangement," which seemed like the "Miscellaneous" box when I'm moving. And that's really one of the book's primary difficulties. If it were only about Powerpoint design, that would be focused and great, or only about report documents, or only about graphs and charts. But Evergreen covers a little of this and a little of that, and so it feels just a little scattered.
My other criticism of the book is Evergreen's tone. I've never seen a textbook where the author is so obsessed with herself, using a very informal, almost flippant, writing style. I don't mind if a textbook isn't as cold and sterile as the standard once required, but my goodness, reading this book often feels like listening to the caffeine-hyped monologue of a college student. I don't need a textbook to tell me I'm a "Rock Star"; I just want information, clearly presented. If this were a normal book in the $20 range, all of this would be fine, and Evergreen could do what she wants. But since it's classified as "textbook," students are paying quite a lot for it—currently $52.13 on Amazon.com. And with that price, I expect a tone that is more respectful toward the reader. I recommend that Sage assign Evergreen a co-author in future editions, to try to temper the voice in the book.
A good thing about the textbook is that the $52.13 gets you full-color pages, which is completely necessary for this topic. I can't believe the first edition of this book wasn't in color! It's a real gift to be able to enjoy the accompanying illustrations to the fullest.
Criticisms aside, Presenting Data Effectively was very helpful for me, and I recommend it to teachers at any level.
November 21, 2015
I was expecting a book about dataviz specifically, but this isn't it.
Here "presenting data" is meant in the sense of document design: putting together reports, slideshows, and posters about your work. How to make the title page look professional? Where do you find images licensed for free use? What combinations of fonts work well for headings vs body text? and so on.
There is some dataviz advice, but it's haphazard, and I disagree with plenty of it.
Evergreen seems to have plenty of solid advice on putting together reports. But since her dataviz advice is often wrong, I can't really trust her on the other matters either.
So I'm glad I skimmed this for the useful tips & resources I did find... But I cannot recommend it as a general resource to someone learning about dataviz (not sure about document design).
Good bits:
* p.12: "Although working memory has limits on its cognitive load, graphic elements can reduce the overload by doing some of the thinking for the reader. By visually organizing and emphasizing information, graphic design makes it more accessible for the reader, increasing the capacity to engage with the words and data. By virtue of this process, richer chunks of information are actually created, which in turn enables the viewer to essentially handle a larger cognitive load at one time."
* p.18: Apparently the International Institute for Information Design site has helpful white papers about info design.
* p.44: If you use Advanced Search in Google Images, you can filter down by copyright status too, to help find images that are OK to reuse.
* The APA Publication Manual apparently has helpful dataviz standards?
* p.66: I didn't know how to find your fonts in Windows. Go to C:\Windows\Fonts and you can see the intended usage category for each font (text, display, decorative, etc.)
* p.88: Free font websites Fontpark and Font Squirrel; and font pairing advice here and here; and an experiment on font trustworthiness
* p.89: Great book title: Type & Layout: Are You Communicating or Just Making Pretty Shapes? :)
* p.98: I didn't know about Adobe Kuler, a free color picker website
* p.116: Not all her dataviz advice is bad: this is a good example of using diverging color schemes for a Likert scale.
Tips for next time I teach dataviz:
* I like her terms "unintentional" and "sloppy." Better than my own vague explanations to students of why alignment should be perfect ("it looks almost aligned but not quite"), just say "You don't want it to look sloppy."
* Show students examples of font substitution in different formats and on different machines. This is why we use PDFs and embed fonts when possible, rather than writing Word docs whose layout can get completely thrown off by using a font unavailable on the reader's machine.
* Talk with students about line length: how many words or characters to fit in a block of text before making a line break? (Apparently 8-12 words, or 50-80 characters.) Useful when deciding where to put text boxes, how to shape them, how many columns to use, etc.
* "Squish and separate" is graphic designers' catchier slang for the Gestalt proximity principle.
* Style sheets are useful. I should review the ones I got from various newspapers when I took Alberto Cairo's dataviz MOOC.
Huh?
* p.67: Do serif fonts really look that bad when projected in slideshows? Check for myself: do my Beamer slides use serifs or sans fonts?
* p.72: She suggests choosing one word in the title to stand out in a decorative font (like an oldey-timey font for the word History in "KCC History Department"). I don't see the point, and it looks unprofessional to my eyes.
* p.85: What exactly is wrong with bullets?
* p.131: You seem to tell me to avoid putting things in the lower-left corner, because of this Gutenberg Diagram thing. But then your next example claims that putting things in that corner is a great example of the Gutenberg advice. What?
Major gripes:
* p.51: No, starting bars above 0 is not "cheating a little bit"---it defeats the whole point of using bars, which is that their lengths are comparable. If you want to zoom in (and not show 0), just use dots instead of bars. Easy. And if you don't understand this, you shouldn't be in the business of doling out dataviz advice.
* p.53: Weird conflicting advice: Don't use 3D because you can't read it easily against the gridlines... Instead, switch to 2D---but also remove the gridlines so that they can't be read at all...? Well, I agree 3D is bad, but this is not a coherent way to argue your point.
* p.85: Oh, now you *do* include 0s, in a scatterplot where all points are far from 0? Why? And why not include a legend for the colors & shapes of these points?
* p.105: Color-blindness is important. But it doesn't help readers to "illustrate" it with awful fuzzy greyscale versions of your images when your book is printed in black-and-white.
* p.110 and many other places: "Go online to this book's website to see this image in color and then keep reading." Nope! That's not how reading a book works. Oh man, and also the text description of colors in her images doesn't match the images at all. Why am I still reading this?
* p.112: AHA, now I get it! She does not care about effective data visualization. She is an infographic designer at heart: look at my giant, colorful "8%" without any context for whether that number higher/lower than average, or the past, or our targets, or anything. This is not about communicating data, just purely about making things "pretty."
Here "presenting data" is meant in the sense of document design: putting together reports, slideshows, and posters about your work. How to make the title page look professional? Where do you find images licensed for free use? What combinations of fonts work well for headings vs body text? and so on.
There is some dataviz advice, but it's haphazard, and I disagree with plenty of it.
Evergreen seems to have plenty of solid advice on putting together reports. But since her dataviz advice is often wrong, I can't really trust her on the other matters either.
So I'm glad I skimmed this for the useful tips & resources I did find... But I cannot recommend it as a general resource to someone learning about dataviz (not sure about document design).
Good bits:
* p.12: "Although working memory has limits on its cognitive load, graphic elements can reduce the overload by doing some of the thinking for the reader. By visually organizing and emphasizing information, graphic design makes it more accessible for the reader, increasing the capacity to engage with the words and data. By virtue of this process, richer chunks of information are actually created, which in turn enables the viewer to essentially handle a larger cognitive load at one time."
* p.18: Apparently the International Institute for Information Design site has helpful white papers about info design.
* p.44: If you use Advanced Search in Google Images, you can filter down by copyright status too, to help find images that are OK to reuse.
* The APA Publication Manual apparently has helpful dataviz standards?
* p.66: I didn't know how to find your fonts in Windows. Go to C:\Windows\Fonts and you can see the intended usage category for each font (text, display, decorative, etc.)
* p.88: Free font websites Fontpark and Font Squirrel; and font pairing advice here and here; and an experiment on font trustworthiness
* p.89: Great book title: Type & Layout: Are You Communicating or Just Making Pretty Shapes? :)
* p.98: I didn't know about Adobe Kuler, a free color picker website
* p.116: Not all her dataviz advice is bad: this is a good example of using diverging color schemes for a Likert scale.
Tips for next time I teach dataviz:
* I like her terms "unintentional" and "sloppy." Better than my own vague explanations to students of why alignment should be perfect ("it looks almost aligned but not quite"), just say "You don't want it to look sloppy."
* Show students examples of font substitution in different formats and on different machines. This is why we use PDFs and embed fonts when possible, rather than writing Word docs whose layout can get completely thrown off by using a font unavailable on the reader's machine.
* Talk with students about line length: how many words or characters to fit in a block of text before making a line break? (Apparently 8-12 words, or 50-80 characters.) Useful when deciding where to put text boxes, how to shape them, how many columns to use, etc.
* "Squish and separate" is graphic designers' catchier slang for the Gestalt proximity principle.
* Style sheets are useful. I should review the ones I got from various newspapers when I took Alberto Cairo's dataviz MOOC.
Huh?
* p.67: Do serif fonts really look that bad when projected in slideshows? Check for myself: do my Beamer slides use serifs or sans fonts?
* p.72: She suggests choosing one word in the title to stand out in a decorative font (like an oldey-timey font for the word History in "KCC History Department"). I don't see the point, and it looks unprofessional to my eyes.
* p.85: What exactly is wrong with bullets?
* p.131: You seem to tell me to avoid putting things in the lower-left corner, because of this Gutenberg Diagram thing. But then your next example claims that putting things in that corner is a great example of the Gutenberg advice. What?
Major gripes:
* p.51: No, starting bars above 0 is not "cheating a little bit"---it defeats the whole point of using bars, which is that their lengths are comparable. If you want to zoom in (and not show 0), just use dots instead of bars. Easy. And if you don't understand this, you shouldn't be in the business of doling out dataviz advice.
* p.53: Weird conflicting advice: Don't use 3D because you can't read it easily against the gridlines... Instead, switch to 2D---but also remove the gridlines so that they can't be read at all...? Well, I agree 3D is bad, but this is not a coherent way to argue your point.
* p.85: Oh, now you *do* include 0s, in a scatterplot where all points are far from 0? Why? And why not include a legend for the colors & shapes of these points?
* p.105: Color-blindness is important. But it doesn't help readers to "illustrate" it with awful fuzzy greyscale versions of your images when your book is printed in black-and-white.
* p.110 and many other places: "Go online to this book's website to see this image in color and then keep reading." Nope! That's not how reading a book works. Oh man, and also the text description of colors in her images doesn't match the images at all. Why am I still reading this?
* p.112: AHA, now I get it! She does not care about effective data visualization. She is an infographic designer at heart: look at my giant, colorful "8%" without any context for whether that number higher/lower than average, or the past, or our targets, or anything. This is not about communicating data, just purely about making things "pretty."
August 27, 2015
This book is an extremely useful tool for learning how to present data visually. It is easy to read with lots of great examples -- not surprising for a book dedicated to effective communication!
February 10, 2019
Written in an engaging, accessible manner, this book is absolutely loaded with tips and tricks to improve presentations. I am inspired by this material! (Yes, a book about data presentation was inspirational!)
November 21, 2019
Excellent book with very practical tips on how to give data so people are excited and engaged. Presents an excellent marriage of the psychology of design with what we see on screens and print. At first, I was skeptical if this kind of presentation technique would work well with science and engineering but I believe it will. Worth the investment.
November 10, 2014
A clear, easy-to-follow guide with practical advice on the presentation of information. Data-based reports and presentations can be useful and engaging!
July 13, 2018
Presenting Data Effectively is a relatively short compact volume on visual research presentation. I expected a book that talked about charts and graphs, however this is more about report presentation. This is still a useful topic that opened me up to thinking about font and color choices in my reports. It was more of an introductory book leaving the reader with just enough information to be dangerous and not enough to be effective.
I appreciate the information she presented on font choices and item placement. I was writing a report while reading this book and I went back to format it to make it more visually appealing. Then I scheduled a meeting with our communications team when I realized I did not yet have the tools to be successful.
It was very frustrating that Evergreen told the reader to look at chart and visualization placement and then published a book that continually had charts and graphics on different pages then when they were referenced in text. I found myself continually flipping through pages. In addition, in the last chapter Evergreen used the word "schizophrenic" as a descriptive for two texts that do not match. Schizophrenia is a word that was created specifically for a mental health diagnosis. To use it in that manner is as offensive as misusing any other categorical identification in a flippant manner. It left a really bad impression and turned me off from reading any other books by Evergreen even though I believe her later works may be more effective then her first book.
I appreciate the information she presented on font choices and item placement. I was writing a report while reading this book and I went back to format it to make it more visually appealing. Then I scheduled a meeting with our communications team when I realized I did not yet have the tools to be successful.
It was very frustrating that Evergreen told the reader to look at chart and visualization placement and then published a book that continually had charts and graphics on different pages then when they were referenced in text. I found myself continually flipping through pages. In addition, in the last chapter Evergreen used the word "schizophrenic" as a descriptive for two texts that do not match. Schizophrenia is a word that was created specifically for a mental health diagnosis. To use it in that manner is as offensive as misusing any other categorical identification in a flippant manner. It left a really bad impression and turned me off from reading any other books by Evergreen even though I believe her later works may be more effective then her first book.
August 15, 2017
I won this as a giveaway. What a disappointment. I was looking forward to enhancing my data presentation skills and I gained very little. My biggest complaint was that there were more "I"s in this book than in some autobiographies I have read. The other major issue with this book is that the author seems to think that charts that show nothing but pictures and very little data are useful. Most of her examples are incomprehensible with just a jumble of unlabled numbers and a huge picture which, in my experience, won't help anyone. One bright spot in this was that she does provide many useful resources that will be of practical help.
July 14, 2018
Evergreen presents a soup-to-nuts compilation of best practices for effectively communicating data to a variety of audiences. This is a great primer for visual rhetoric and making complex information clear, understandable, and actionable.
The second edition includes many more examples and illustrations. I highly recommend getting the second edition (even if you have the 1st edition).
The second edition includes many more examples and illustrations. I highly recommend getting the second edition (even if you have the 1st edition).
March 20, 2018
Excellent! It takes a lot of the intuitive things I have sensed about good presentations and designs and put them into a book as a set of instructions. Very good for an up and coming grad student.
January 11, 2019
Good...but most of this information is available from elsewhere.
November 4, 2019
Didn't really read anything I hadn't already seen in other books.
Read
February 1, 2020001.4226 E934 2018
November 29, 2020
Lots of good information, helpfully organized. The first three chapters in particular had a tremendous amount of advice for improving the way we present data and reports.
December 19, 2022
It's been almost 4 years since I first read this book and I would love to see a Third Edition. But whatever editions there are, I will continue to read and refer to Evergreen's guidance.
August 31, 2016
For a long time, I wrote off data reporting/charts as an annoying part of my work. I'd rather spend my time analyzing data and finding things that could move my organization forward. This book has convinced me that quality presentation is incredibly important for making your work stand out, especially to the lay audience.
What convinced me? Evergreen backs up her rationale for design with cognitive science and research into graphic design. Whether you're putting together a report, a presentation, or a poster, you can make deliberate choices in the design that can help make your work easier for your audience to understand because that's the way their brain works.
I think my main reason for hating formatting/presentation is that I didn't have a system. Evergreen lowers the bar for entry into proper design by explaining why you should make certain choices around font, color, alignment, and more. If you flip your viewpoint from, "this report will look pretty" to "the information will be presented in a way that focuses reader cognition on my message rather than my formatting", then this work feels pretty compelling.
If you hate presenting data or simply need a guide on how to do it well, this is a book for you.
What convinced me? Evergreen backs up her rationale for design with cognitive science and research into graphic design. Whether you're putting together a report, a presentation, or a poster, you can make deliberate choices in the design that can help make your work easier for your audience to understand because that's the way their brain works.
I think my main reason for hating formatting/presentation is that I didn't have a system. Evergreen lowers the bar for entry into proper design by explaining why you should make certain choices around font, color, alignment, and more. If you flip your viewpoint from, "this report will look pretty" to "the information will be presented in a way that focuses reader cognition on my message rather than my formatting", then this work feels pretty compelling.
If you hate presenting data or simply need a guide on how to do it well, this is a book for you.
June 28, 2016
A great small easy to read and visual book which differentiates very helpfully between Reports, Slideshows, Posters, Data Displays, and Online data. The visuals are always relevant and the chapter summaries are invaluable; the further links are brilliant and the actual suggestions of trying it out are very relevant. Brilliant book for beginners who need an overview of design principles focussed on presenting data
January 17, 2014
Easy to understand, relevant to every undergraduate, and with direct applications to the software most of us use: Microsoft Office
April 28, 2015
Great data visualization resource. Goes beyond just charts and graphs to overall report formats, etc. A great addition to my data geek bookshelf.
Read
May 26, 2018Not really about presenting data, but a good document and deck design book anyway.
Displaying 1 - 20 of 20 reviews