Lecture ON 06

Uni Studies 3:The Visual Display of Quantitative Information:Graphical Integrity

Assoc. Professor Donald J. PattersonUni Stu 3 Fall 2012

1Thursday, November 8, 12

The Visual Display of Quantitative Information

Graphical Excellence is the well-designed presentation of interesting

data

substance statistics design

consists of complex ideas communicated with clarity precision efciency

is that which gives the viewer the greatest number of ideas in the shortest time with the least ink

Thursday, November 8, 12

Graphical Excellence begins with Graphical Integrity



Graphical Integrity not lying with statistics tell the truth about data



Examples of Infographics lacking integrityThe Visual Display of Quantitative Information

Day Mines, Inc., 1974 Annual Report



Day Mines, Inc., 1974 Annual Report

-$4,200,000



New York Times, 8/8/78


Lets formalize Distortion in Infographics





Perceived = Actualx




Perceived = Actualx x = .8 .3



Perceived Area grows more slowly than measured area varies between people changes with experience changes with context changes with loading



Guidelines The measurement of the graphic should be in

proportion to the quantity

Clear, detailed labels should explain distortion and events, on the graphic.

LieFactor =size of eect shown in graphic

size of eect in data



New York Times, 8/9/78

LieFactor = 14.8



Past and Future are reversed Foreshortening is confusing two issues Y-Scale is crazy



Design vs Data VariationWe expect that patterns will continue

Dont confuse design variation and data variation



NSF, 1974



New York Times,

12/19/78

design variationLieFactor = 15.1



Time 4/9/79

design variation

454% in data 4280% in graphic

LieFactor = 9.4



design variation

708% in data 6700% in graphic

LieFactor = 9.5



Good examples adjusted dollar amounts for ination




Business Week

4/9/1979Thursday, November 8, 12


Bad example



Done well Adjusted for ination Adjusted for population No chart junk



Context is essential for graphical integrityGraphics must not quote data out of context



Summary The size of the graphic should match the size of the

quantity

Labels, explanations and events should be on the graph

Data variation should dominate, not design variation Time-series with money should be ination adjusted

and standardized

The number of dimensions of data should match the number of dimensions in the graphic

Graphics should be put in context

LieFactor = 1.0


Documents

Lecture ON 06