Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 0 Displaying Quantitative Information An exploration of Edward R. Tufte’s The Visual.

Slides:



Advertisements
Similar presentations
ENV Envisioning Information Lecture 8 – Good Design – What we can learn from Tufte Ken Brodlie
Advertisements

Lecture 06: Design II February 5, 2013 COMP Visualization.
Theory of Data Graphics Part 1 Most of a graphic’s ink should vary in response to data variation (see chapters 4-6)
Lecture 1: Beautiful graphics in R
© Keith Vander Linden, 1999 “A picture is worth a thousand words”
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 2-4 Statistical Graphics.
Introduction to Data Analytics
© Anselm Spoerri Lecture 4 Human Visual System –Recap –3D vs 2D Debate –Object Recognition Theories Tufte – Envisioning Information.
1 Some principles of graphical excellence Kaye E. Marion Norca Consulting Pty Ltd Principle reference: Tufte, E.R. (1983), The visual display of quantitative.
Data Presentation A guide to good graphics Bureau of Justice Statistics Marianne W. Zawitz.
1 Information Design Scott Matthews Courses: /
Source: Tufte E. (2001) The Visual Display of Quantitiative Information. 2 nd Ed. Cheshire: Graphics Press Originally published in American Education,
Mathematics for all: sense and nonsense of statistical representations Heleen Verhage, Freudenthal Institute PME25 Summer Institute, July 2001.
Introduction to Descriptive Statistics Spring 2007.
Scientific Communication and Technological Failure presentation for ILTM, July 9, 1998 Dan Little.
Introduction to Descriptive Statistics Spring 2006.
LSP 120: Quantitative Reasoning and Technological Literacy Section 903 Özlem Elgün.
Design World Graphical Integrity
PSY 1950 Graph Design December 8, Why graph? Exploratory data analysis –Usually raw data –Tukey: a good graph “forces us to notice what we never.
1 Information Design Scott Matthews Courses: /
Data Visualization.
1 SCIP Africa Summit | October , 2014 Competitive Analysis Techniques Choosing the right visual tools for CI and decision-making.
ID-2050 The “Design” Lecture. Today Document Design Information Design Tufte’s “Data Maps” BREAK Graphical Excellence in practice.
The Oral Presentation Kim E. Barrett, Ph.D. Professor of Medicine and Vice Chair for Research Department of Medicine University of California, San Diego,
1 Determining Effective Data Display with Charts.
Information Visualization in Data Mining S.T. Balke Department of Chemical Engineering and Applied Chemistry University of Toronto.
LSP 120: Quantitative Reasoning and Technological Literacy Özlem Elgün Prepared by Ozlem Elgun1.
Tufte’s Design Principles
Infographics Visualizing Data. What are they? InfographicsInfographics can be used to visualize data in beautiful and interesting ways making it fun and.
Graphics and visual information English 314 Technical communication Note: To hide or reveal these lecture notes, go to VIEW and click COMMENTS. This lecture.
Computing & Information Sciences Kansas State University CIS 536/636 Introduction to Computer Graphics Lecture 34 of 41 William H. Hsu Department of Computing.
Visualizing quantitative information martin krzywinski.
Principles of Graphical Excellence Best Paper: ALAIR April 5–6, 2001 AIR: June 2-5, 2002, Toronto Focus-IR, February 21, 2003 Anna T. Waggener, Ph.D. Institutional.
Making Graphs. The Basics … Graphical Displays Should: induce the viewer to think about the substance rather than about the methodology, graphic design,
Data Visualization TIME Training Neuhausen, 1-5 September 2014.
Mark P. Baldwin Northwest Research Associates, USA Cargese UTLS Summer School, 6 Oct Data Graphics AndTypography.
Tutor: Prof. A. Taleb-Bendiab Contact: Telephone: +44 (0) CMPDLLM002 Research Methods Lecture 9: Quantitative.
The Center for IDEA Early Childhood Data Systems April 25, 2014 Data Visualization: A Picture’s Worth a Thousand Numbers Nick Ortiz, Alice Ridgway and.
Mark P. Baldwin Northwest Research Associates, USA Cargese UTLS Summer School, 6 Oct Data Graphics AndTypography.
Graphical Analysis. Why Graph Data? Graphical methods Require very little training Easy to use Massive amounts of data can be presented more readily Can.
ACOT Intro/Copyright Succeeding in Business with Microsoft Excel 2010: Chapter1.
Principles of Good Presentation Slides & Graphics November 21, 2008 Adapted from slides used by Katie Kopren.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Graphical Display and Presentation of Quantitative Information 13 February 2006.
Quantitative Skills 1: Graphing
Representing Data Sets MCC9–12.S.ID.1. Data can be represented graphically using a__________. Graphs provide a visual representation of data; just by.
1 Eric Rasmusen, March 10, 2014 Graphs and Tables.
Graphics for Macroeconomics. Principles Graphing is done best when it clearly communicates ideas about data Focus on the main point while preventing distractions.
Introduction to Graphical Presentation Andy Wang CIS Computer Systems Performance Analysis.
© 1998, Geoff Kuenning The Art of Graphical Presentation Types of Variables Guidelines for Good Graphics Charts Common Mistakes in Graphics Pictorial Games.
CHAPTER 20 Representing Quantitative Data. Why ‘re’present your numbers? Few people can extract meaning from arrays of numbers. Summarising them – whether.
MIS2502: Data Analytics Principles of Data Visualization David Schuff
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
COMMUNICATING DATA USING GRAPHICS MIS2502 Data Analytics.
Four types Data maps (17-19, Tufte, also History of the World in 100 Seconds)History of the World in 100 Seconds Time series Narrative graphics of space.
1 CSE 2337 Chapter 3 Data Visualization With Excel.
Information Design Trends Unit Three: Information Visualization Lecture 1: Escaping Flatland.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 4-2 Displaying Distributions with Graphs.
MIS2502: Data Analytics Principles of Data Visualization.
Recap Iterative and Combination of Data Visualization Unique Requirements of Project Avoid to take much Data Audience of Problem.
United Nations Economic Commission for Europe Statistical Division Making data meaningful through effective visual presentation.
Infographic (informational graphic) Edward TufteEdward Tufte in The Visual Display of Quantitative Information defines 'graphical displays' in the following.
Statistics Review  Mode: the number that occurs most frequently in the data set (could have more than 1)  Median : the value when the data set is listed.
DATA VISUALIZATION BOB MARSHALL, MD MPH MISM FAAFP FACULTY, DOD CLINICAL INFORMATICS FELLOWSHIP.
Dot Plots and Histograms SWBAT REPRESENT DATA USING DOT PLOTS AND HISTOGRAMS. SWBAT ANALYZE AND INTERPRET DATA ON A DOT PLOT AND HISTOGRAM BY FINDING MEAN,
Data Visualization.
More on Data Presentation CS 239 Experimental Methodologies for System Software Peter Reiher May 24, 2007.
What’s the problem? Goodson
Presentation transcript:

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 0 Displaying Quantitative Information An exploration of Edward R. Tufte’s The Visual Display of Quantitative Information Jeffrey Nichols Programming Usable Interfaces May 2, 2003

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 1 Good graphics Napolean’s invasion of Russia, as drawn by Charles Joseph Minard ( )

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 2 More good graphics The price of wheat compared to labour wages, William Playfair ( )

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 3 More good graphics French train schedule, as drawn by E.J. Marey ( )

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 4 More good graphics Map of the northern galactic hemisphere (1.3 million galaxies shown)

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 5 What made these graphics good?

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 6 Bad graphics

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 7 More bad graphics

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 8 More bad graphics

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 9 More bad graphics

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 10 More bad USA Today Graphs

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 11 What made these graphics bad?

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 12 How can we make better graphics? Tufte presents some principles of data graphics  Above all else, show the data.  Maximize the data-ink ratio  Erase non-data-ink  Erase redundant data-ink  Revise and edit

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 13 Above all else, show the data

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 14 Show the data

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 15 Data-Ink  Ink that changes as the data changes  Non-redundant ink!

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 16 Data-Ink Ratio Data-ink ratio = data-ink Total ink used to print graphic =Proportion of a graphic’s ink devoted to the non-redundant display of data-information. =1.0 – proportion of graphic that can be erased without the loss of information

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 17 Ratio of Histogram What is the data-ink ratio of this graphic? < 0.05 !!!

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 18 Ratio of USA Today Graphic  What is the data-ink ratio of this graphic? < 0.001

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 19 How can we make better graphics? Tufte presents some principles of data graphics  Above all else, show the data.  Maximize the data-ink ratio  Within reason  Every bit of ink on a graphic requires a reason  Erase non-data-ink  Erase redundant data-ink  Revise and edit

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 20 How can we make better graphics? Tufte presents some principles of data graphics  Above all else, show the data.  Maximize the data-ink ratio  Erase non-data-ink  Erase redundant data-ink  Revise and edit

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 21 Erase non-data-ink, within reason

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 22 Erase non-data-ink, within reason

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 23 Erase non-data-ink, within reason Histogram of Midterm Results Scoring Buckets # of Students C B- B B+ A- A

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 24 Erase redundant data-ink Histogram of Midterm Results Scoring Buckets # of Students C B- B B+ A- A

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 25 Erase redundant data-ink Histogram of Midterm Results Scoring Buckets # of Students C B- B B+ A- A What’s the data-ink ratio?

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 26 How can we make better graphics? Tufte presents some principles of data graphics  Above all else, show the data.  Maximize the data-ink ratio  Erase non-data-ink  Erase redundant data-ink  Revise and edit

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 27 The Principles Applied to Common Forms Box Plots Median 75% 25% Maximum Minimum

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 28 The Principles Applied to Common Forms Box Plots Median 75% 25% Maximum Minimum

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 29 The Principles Applied to Common Forms Bar Graphs Original Graph Modified Graph

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 30 The Principles Applied to Common Forms Scatter Plots Original Graph Modified Graph

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 31 The Principles Applied to Common Forms Another Scatter Plot Variant

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 32 Conclusions  Show data variation, not design variation  Avoid using ink for non-data items  Avoid redundancy  Clear and detailed labeling should be used to defeat graphical distortion  Revise and Edit

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 33 Questions?

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 34 Thanks for a great class! Reminder: Final Exam on Friday, May 9 th at 8:30am in this room

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 35 More Bad USA Today Graphs

Jeffrey Nichols Displaying Quantitative Information May 2, 2003 Slide 36 Tufte’s Principles  Graphical Integrity  The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented.  Clear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data.  Show data variation, not design variation.  In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.  The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data.  Graphics must not quote the data out of context.  Theory of Data Graphics  Above all else, show the data.  Maximize the data-ink ratio  Erase non-data-ink  Erase redundant data-ink  Revise and edit  Other comments  Graphical elegance is often found in simplicity of design and complexity of data  Data graphics are paragraphs about data and should be treated as such