© 1998, Geoff Kuenning The Art of Graphical Presentation Types of Variables Guidelines for Good Graphics Charts Common Mistakes in Graphics Pictorial Games.

© 1998, Geoff Kuenning

The Art of Graphical Presentation

• Types of Variables• Guidelines for Good Graphics Charts• Common Mistakes in Graphics• Pictorial Games• Special-Purpose Charts


Types of Variables

• Qualitative– Ordered (e.g., modem, Ethernet,

satellite)– Unordered (e.g., CS, math, literature)

• Quantitative– Discrete (e.g., number of terminals)– Continuous (e.g., time)


Charting Based on Variable Types

• Qualitative variables usually work best with bar charts or Kiviat graphs– If ordered, use bar charts to show order

• Quantitative variables work well in X-Y graphs– Use points if discrete, lines if continuous– Bar charts sometimes work well for

discrete


Guidelines for Good Graphics Charts

• Principles of graphical excellence• Principles of good graphics• Specific hints for specific situations• Aesthetics• Friendliness


Principlesof Graphical Excellence

• Graphical excellence is the well-designed presentation of interesting data:– Substance– Statistics– Design


Graphical Excellence (2)

• Complex ideas get communicated with:– Clarity– Precision– Efficiency



• Viewer gets:– Greatest number of ideas– In the shortest time– With the least ink– In the smallest space



• Is nearly always multivariate• Requires telling truth about data


Principles of Good Graphics

• Above all else show the data• Maximize the data-ink ratio• Erase non-data ink• Erase redundant data ink• Revise and edit


Above All ElseShow the Data

y = 1E-05x + 1.3641

R2 = 0.0033

0

1

2

3

4

5

0 5000 10000 15000File size (bytes)

Tim

e to

fet

ch (

seco

nds) Linear model


Above All ElseShow the Data

y = 1E-05x + 1.3641

R2 = 0.0033

0

1

2

3

4

5

0 5000 10000 15000File size (bytes)

Tim

e to

fet

ch (

seco

nds) Linear model


Maximize theData-Ink Ratio

1st Qtr

3rd Qtr

010203040506070

80

90

East

West

North


Maximize theData-Ink Ratio

0

20

40

60

80

100

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

East West

North


Erase Non-Data Ink

05

1015202530354045505560657075808590


East

West

North


Erase Non-Data Ink

0

20

40

60

80


Eas

t

Wes

t

Nor

th


Erase Redundant Data Ink

20.4

27.4

90

20.4

38.634.6

31.6

46.9 45 43.9

30.6

45.9

0

20

40

60

80


Eas

t

Wes

t

Nor

th


Erase Redundant Data Ink

0

20

40

60

80


Eas

t

Wes

t

Nor

th


Revise and Edit

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr0

20

40

60

80

100


Default Microsoft Powerpoint Chart

East

West

North


Revise and Edit

Remove Decorative Effects

0102030405060708090


East

West

North


Revise and Edit

Remove Clutter

0102030405060708090


East

West

North


Revise and Edit

Make Legend Simple to Interpret

0102030405060708090


East

West

North


Revise and Edit

Eliminate Superfluous Ink

0

20

40

60

80

100


East

West

North


Revise and Edit

Eliminate Red/Green Distinctions

0

20

40

60

80

100


East

West

North


Specific Things to Do

• Give information the reader needs• Limit complexity and confusion• Have a point• Show statistics graphically• Don’t always use graphics• Discuss it in the text


Give Informationthe Reader Needs

• Show informative axes– Use axes to indicate range

• Label things fully and intelligently• Highlight important points on the graph


Giving Informationthe Reader Needs

0

20

40

60

80

1 2 3 4

E

W

N


Giving Informationthe Reader Needs

0

20

40

60

80


Salesin

Millions

MicrosoftContractSigned

East

North

West


Limit Complexityand Confusion

• Not too many curves• Single scale for all curves• No “extra” curves• No pointless decoration (“ducks”)


0

10

20

30

40

50

60


0102030405060708090100 West

North

Northeast

Southwest

Mexico

Europe

Japan

East

South

International

Limiting Complexityand Confusion


International Sales

0

20

40

60

80

100


Millionsof

Dollars

Japan

Mexico

Europe

Limiting Complexityand Confusion


Have a Point

• Graphs should add information not otherwise available to reader

• Don’t plot data just because you collected it

• Know what you’re trying to show, and make sure the graph shows it


Having a Point

• Sales were up 15% this quarter:

0

20

40

60

80

100

120

1st Qtr 2nd Qtr


Having a Point

User Time of Copy Benchmarks

0

0.01

0.02

0.03

0.04

1 Replica 2 Replicas 3 Replicas 4 Replicas

cp rcp


Having a Point

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

Modem Ethernet ATM Satellite

Throughput

Latency


Having a Point

1

10

100

1000

10000

100000

1000000

0.01 0.1 1 10 100 1000

Throughput (Kbits/sec)

Latency( s) Ethernet

Modem

ATM

Satellite


Show Statistics Graphically

• Put bars in a reasonable order– Geographical– Best to worst– Even alphabetic

• Make bar widths reflect interval widths– Hard to do with most graphing software

• Show confidence intervals on the graph– Examples will be shown later


Don’t AlwaysUse Graphics

• Tables are best for small sets of numbers– e.g., 20 or fewer

• Also best for certain arrangements of data– e.g., 10 graphs of 3 points each

• Sometimes a simple sentence will do• Always ask whether the chart is the best way

to present the information– And whether it brings out your message


Text Would HaveBeen Better

Dem Rep Indep

Carter

Reagan

Anderson

Lib Mod Cons

LibDems

ModDems

ConsDems

LibInd

ModInd

ConsInd


Discuss It in the Text

• Figures should be self-explanatory– Many people scan papers, just look at

graphs– Good graphs build interest, “hook” readers

• But text should highlight and aid figures– Tell readers when to look at figures– Point out what figure is telling them– Expand on what figure has to say


Aesthetics

• Not everyone is an artist– But figures should be visually

pleasing• Elegance is found in

– Simplicity of design– Complexity of data


Principles of Aesthetics

• Use appropriate format and design• Use words, numbers, drawings together• Reflect balance, proportion, relevant scale• Keep detail and complexity accessible• Have a story about the data (narrative quality)• Do a professional job of drawing• Avoid decoration and chartjunk


Use Words, Numbers, Drawings Together

• Put graphics near or in text that discusses them– Even if you have to murder your word

processor• Integrate text into graphics• Tufte: “Data graphics are paragraphs

about data and should be treated as such”


Reflect Balance, Proportion, Relevant Scale

• Much of this boils down to “artistic sense”• Make sure things are big enough to read

– Tiny type is OK only for young people!• Keep lines thin

– But use heavier lines to indicate important information

• Keep horizontal larger than vertical– About 50% larger works well


Poor Balanceand Proportion

• Sales in the North and West districts were steady through all quarters

• East sales varied widely, significantly outperforming the other districts in the third quarter

0

10

20

30

40

50

60

70

80

90

100



Better Proportion

• Sales in the North and West districts were steady through all quarters

• East sales varied widely, significantly outperforming the other districts in the third quarter

0

50

100

Q1 Q2 Q3 Q4


Keep Detail and Complexity Accessible

Make your graphics friendly:– Avoid abbreviations and encodings– Run words left-to-right– Explain data with little messages– Label graphic, don’t use elaborate

shadings and a complex legend– Avoid red/green distinctions– Use clean, serif fonts in mixed case


An Unfriendly Graph

0

50

100

150

200

250

300

350

400

450

1 REPL 3 5 7

Tim

e

CP

FIND

FINDGREP

GREP

LS

MAB

RCP

RM


A Friendly Version

0

100

200

300

400

1 2 3 4 5 6 7 8

Number of Replicas

Time in Seconds

Copy

Compile

Remove

Note almost no growth incompile/remove times


Even Friendlier

0

100

200

300

400

Copy Compile Remove

Benchmark and Number of Replicas

Time in Seconds

Note slower growth incompile and remove times

1 Replica

8 Replicas(note departurefrom linearity)


Have a Story About the Data (Narrative Quality)

• May be difficult in technical papers• But think about why you are drawing graph• Example:

– Performance is controlled by network speed

– But it tops out at the high end– And that’s because we hit a CPU

bottleneck


Showing a StoryAbout the Data

0

20

40

60

0 2 4 6 8 10

Network Bandwidth (Mbps)

Transactionsper

Second CPU bottleneckreached


Do a Professional Jobof Drawing

• This is easy with modern tools– But take the time to do it right

• Align things carefully• Check the final version in the format you will

use– I.e., print the Postscript one last time

before submission– Or look at your slides on the projection

screen


Avoid Decorationand Chartjunk

• Powerpoint, etc. make chartjunk easy• Avoid clip art, automatic backgrounds, etc.• Remember: the data is the story

– Statistics aren’t boring– Uninterested readers aren’t drawn by

cartoons– Interested readers are distracted

• Does removing it change the message?– If not, leave it out


Examples of Chartjunk

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr0

10

20

30

40

50

60

70

80

90


Gridlines!Vibration

Pointless

Fake 3-D Effects

Filled “Floor” Clip Art

In or out?

Filled

“Walls”

Borders and

Fills Galore

Unintentional

Heavy or Double Lines

Filled Labels


Common Mistakes in Graphics

• Excess information• Multiple scales• Using symbols in place of text• Poor scales• Using lines incorrectly


Excess Information

• Sneaky trick to meet length limits• Rules of thumb:

– 6 curves on line chart– 10 bars on bar chart– 8 slices on pie chart

• Extract essence, don’t cram things in


Way Too Much Information

0

100

200

300

400

500

1 REPL 2 3 4 5 6 7 8

Time

cp

find

findgrep

grep

ls

mab

rcp

rm


What’s ImportantAbout That Chart?

• Times for cp and rcp rise with number of replicas

• Most other benchmarks are near constant

• Exactly constant for rm


The Right Amountof Information

0

100

200

300

400

500

0 1 2 3 4 5 6 7 8 9Replicas

Timecp

mab

rm


Multiple Scales

• Another way to meet length limits• Basically, two graphs overlaid on each other• Confuses reader (which line goes with which

scale?)• Misstates relationships

– Implies equality of magnitude that doesn’t exist


Some Especially Bad Multiple Scales

0

5

10

15

20

25

30

35

40

45

1 2 3 4

10

100

1000

Throughput

Response Time


Using Symbolsin Place of Text

• Graphics should be self-explanatory– Remember that the graphs often draw

the reader in• So use explanatory text, not symbols• This means no Greek letters!

– Unless your conference is in Athens...


It’s All Greek To Me...

0

2

4

6

8

10

12

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

w


Explanation is Easy

Waiting Time asa Function of Offered Load

0

2

4

6

8

10

12

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Offered Load

Waiting Time


Poor Scales

• Plotting programs love non-zero origins– But people are used to zero

• Fiddle with axis ranges (and logarithms) to get your message across– But don’t lie or cheat

• Sometimes trimming off high ends makes things clearer– Brings out low-end detail


Nonzero Origins(Chosen by Microsoft)

65

70

75

80

85

90

95



Proper Origins

0102030405060708090

100



A Poor Axis Range

0

2000

4000

6000

8000

10000

12000

1 2 3 4


A Logarithmic Range

1

10

100

1000

10000

1 2 3 4


A Truncated Range

0

10

20

30

40

50

60

1 2 3 4

10000


Using Lines Incorrectly

• Don’t connect points unless interpolation is meaningful

• Don’t smooth lines that are based on samples– Exception: fitted non-linear curves


Incorrect Line Usage

0

100

200

300

400

500

0 1 2 3 4 5 6 7 8 9Replicas

Timecp

mab

rm


Pictorial Games

• Non-zero origins and broken scales• Double-whammy graphs• Omitting confidence intervals• Scaling by height, not area• Poor histogram cell size


Non-Zero Originsand Broken Scales

• People expect (0,0) origins– Subconsciously

• So non-zero origins are a great way to lie• More common than not in popular press• Also very common to cheat by omitting

part of scale– “Really, Your Honor, I included (0,0)”


Non-Zero Origins

20

21

22

23

24

25

26

27


UsThem

0

20

40

60

80

100

1st Qtr 2ndQtr

3rdQtr

4th Qtr

ThemUs


The Three-Quarters Rule

• Highest point should be 3/4 of scale or more

0

5

10

15

20

25

30


ThemUs


Double-Whammy Graphs

• Put two related measures on same graph– One is (almost) function of other

• Hits reader twice with same information– And thus overstates impact

0

20

40

60


Sales ($)

Units Shipped


OmittingConfidence Intervals

• Statistical data is inherently fuzzy• But means appear precise• Giving confidence intervals can make it

clear there’s no real difference– So liars and fools leave them out


Graph WithoutConfidence Intervals

0

10

20

30

40

50

60

70



Graph WithConfidence Intervals

0

10

20

30

40

50

60

70



Confidence Intervals

• Sample mean value is only an estimate of the true population mean

• Bounds c1 and c2 such that there is a high probability, 1-, that the population mean is in the interval (c1,c2):

Prob{ c1 < < c2} =1- where is the significance level and100(1-) is the confidence level

• Overlapping confidence intervals is interpreted as “not statistically different”


Graph WithConfidence Intervals

0

10

20

30

40

50

60

70



Scaling by HeightInstead of Area

• Clip art is popular with illustrators:

Women in the Workforce

1960 1980


The Troublewith Height Scaling

• Previous graph had heights of 2:1• But people perceive areas, not heights

– So areas should be what’s proportional to data• Tufte defines a lie factor: size of effect in graphic

divided by size of effect in data– Not limited to area scaling– But especially insidious there (quadratic effect)


Scaling by Area

• Here’s the same graph with 2:1 area:

Women in the Workforce

1960 1980


Poor Histogram Cell Size

• Picking bucket size is always a problem• Prefer 5 or more observations per bucket• Choice of bucket size can affect results:

02468

1012

5 10 15 20 25 30


Special-Purpose Charts

• Histograms• Scatter plots• Gantt charts• Kiviat graphs


Histograms

0

20

40

60

80



Scatter Plots

• Useful in statistical analysis• Also excellent for huge quantities of data

– Can show patterns otherwise invisible

0

5

10

15

20

25

0 5 10 15


Gantt Charts

• Shows relative duration of Boolean conditions• Arranged to make lines continuous

– Each level after first follows FTTF pattern

0 20 40 60 80 100

CPU

I/O

Network


Kiviat Graphs

• Also called “star charts” or “radar plots”• Useful for looking at balance between HB and

LB metrics


Useful Reference Works

• Edward R. Tufte, The Visual Display of Quantitative Information, Graphics Press, Cheshire, Connecticut, 1983.

• Edward R. Tufte, Envisioning Information, Graphics Press, Cheshire, Connecticut, 1990.

• Edward R. Tufte, Visual Explanations, Graphics Press, Cheshire, Connecticut, 1997.

• Darrell Huff, How to Lie With Statistics, W.W. Norton & Co., New York, 1954

© 1998, Geoff Kuenning The Art of Graphical Presentation Types of Variables Guidelines for Good Graphics Charts Common Mistakes in Graphics Pictorial Games.

Documents