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Introduction to Graphical Presentation. Andy Wang CIS 5930-03 Computer Systems Performance Analysis. The Art of Graphical Presentation. Reference Works Types of Variables Guidelines for Good Graphics Charts Common Mistakes in Graphics Pictorial Games Special-Purpose Charts.

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Introduction to graphical presentation l.jpg

Introduction toGraphical Presentation

Andy Wang

CIS 5930-03

Computer Systems

Performance Analysis


The art of graphical presentation l.jpg
The Art of Graphical Presentation

  • Reference Works

  • Types of Variables

  • Guidelines for Good Graphics Charts

  • Common Mistakes in Graphics

  • Pictorial Games

  • Special-Purpose Charts


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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


Types of variables l.jpg
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)


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Charting Basedon 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


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Guidelines for Good Graphics Charts

  • Principles of graphical excellence

  • Principles of good graphics

  • Specific hints for specific situations

  • Aesthetics

  • Friendliness


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Principlesof Graphical Excellence

  • Graphical excellence is the well-designed presentation of interesting data:

    • Substance

    • Statistics

    • Design


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Graphical Excellence (2)

  • Complex ideas get communicated with:

    • Clarity

    • Precision

    • Efficiency


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Graphical Excellence (3)

  • Viewer gets:

    • Greatest number of ideas

    • In the shortest time

    • With the least ink

    • In the smallest space


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Graphical Excellence (4)

  • Is nearly always multivariate

  • Requires telling truth about data


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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


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Above All ElseShow the Data


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Above All ElseShow the Data


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Maximize theData-Ink Ratio


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Maximize theData-Ink Ratio



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Erase Non-Data Ink

North

West

East


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Erase Redundant Data Ink

North

West

East


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Erase Redundant Data Ink

North

West

East









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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


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Give Informationthe Reader Needs

  • Show informative axes

    • Use axes to indicate range

  • Label things fully and intelligently

  • Highlight important points on the graph


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Giving Informationthe Reader Needs


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Giving Informationthe Reader Needs


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Limit Complexityand Confusion

  • Not too many curves

  • Single scale for all curves

  • No “extra” curves

  • No pointless decoration (“ducks”)


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Limiting Complexityand Confusion


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Limiting Complexityand Confusion


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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


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Having a Point

  • Sales were up 15% this quarter:





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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


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Don’t AlwaysUse Graphics

  • Tables are best for small sets of numbers

    • Tufte says 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


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Text Would HaveBeen Better


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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


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Aesthetics

  • Not everyone is an artist

    • But figures should be visually pleasing

  • Elegance is found in

    • Simplicity of design

    • Complexity of data


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Principles of Aesthetics

  • Use appropriate format and design

  • Use words, numbers, drawings together

  • Reflect balance, proportion, relevant scale

  • Keep detail and complexity accessible

  • Have story about the data (narrative quality)

  • Do professional job of drawing

  • Avoid decoration and chartjunk


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Use AppropriateFormat and Design

  • Don’t automatically draw a graph

    • Mentioned before

  • Choose graphical format carefully

  • Sometimes “text graphic” works best

    • Use text placement to communicate numbers

    • Very close to being a table


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CEA: +4.7

WEF: 6.8

DR: +4.5

CB: 6.7

NABE: +4.5

NABE: 6.7

WEF: +4.5

IBM: 6.6

CBO: +4.4

DR: 6.5

CB: +4.2

NABE: +6.2

CBO: 6.3

IBM: +4.1

IBM: +5.9

WEF: +21

CEA: 6.3

GNP: +3.8

IPG: +5.8

CPI: +7.7

Profits: +13.3

Unempl: 6.0

CE: +2.9

CB: +5.5

IBM: +6.6

DR: +10.5

DR: +5.2

NABE: +6.5

IBM: +10.4

WEF: +4.8

CB: +6.2

CE: +6.5

Using Text as a Graphic

About a year ago, eight forecasters were asked for

their predictions on some key economic indicators.

Here’s how the forecasts stack up against the

probable 1978 results (shown in the black panel).

(New York Times,

Jan. 2, 1979)


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The Stem-and-Leaf Plot

  • From Tukey, via Tufte, heights of volcanoes in feet:0|98766562 1|97719630 2|99987766544422211009850 3|876655412099551426 4|9998844331929433361107 5|97666666554422210097731 6|898665441077761065 7|98855431100652108073 8|653322122937


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Choosinga Graphical Format

  • Many options, more being invented all the time

    • Examples will be given later

    • See Jain for some commonly useful ones

    • Tufte shows ways to get creative

  • Choose a format that reflects your data

    • Or that helps you analyze it yourself


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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”


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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


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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


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Better Proportion

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

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


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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





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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 high end

    • And that’s because we hit a CPU bottleneck


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Showing a StoryAbout the Data


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Do a Professional Jobof Drawing

  • This is easy with modern tools

    • But take the time to do it right

  • Align things carefully

  • Check final version in format you will use

    • I.e., print Postscript one last time before submission

    • Or look at your slides on projection screen

      • Preferably in presentation room

      • Color balance varies by projector


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Avoid Decorationand Chartjunk

  • Powerpoint, etc. make chartjunk easy

  • Avoid clip art, automatic backgrounds, etc.

  • Remember: data is the story

    • Statistics aren’t boring

    • Uninterested readers aren’t drawn by cartoons

    • Interested readers are distracted

  • Does removing it change message?

    • If not, leave it out


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Examples of Chartjunk

In or out?

Filled Labels

Borders and

Fills Galore

Pointless

Fake 3-D Effects

Gridlines!

Vibration

Filled

“Walls”

Unintentional

Heavy or Double Lines

Serif Font with

Thin & Thick Lines

Filled “Floor”

Clip Art


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Common Mistakesin Graphics

  • Excess information

  • Multiple scales

  • Using symbols in place of text

  • Poor scales

  • Using lines incorrectly


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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

      • But note that Tufte hates pie charts

  • Extract essence, don’t cram things in



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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


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The Right Amountof Information


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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



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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...




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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





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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



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Pictorial Games

  • Non-zero origins and broken scales

  • Double-whammy graphs

  • Omitting confidence intervals

  • Scaling by height, not area

  • Poor histogram cell size


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Non-Zero Originsand Broken Scales

  • People expect (0,0) origins

    • Subconsciously

  • So non-zero origins are 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)”



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The Three-Quarters Rule

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


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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


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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


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Graph WithoutConfidence Intervals


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Graph WithConfidence Intervals


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1960

1980

Scaling by HeightInstead of Area

  • Clip art is popular with illustrators:

Women in the Workforce


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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 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 l.jpg

1960

1980

Scaling by Area

  • Same graph with 2:1 area:

Women in the Workforce


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Poor Histogram Cell Size

  • Picking bucket size is always problem

  • Prefer 5 or more observations per bucket

  • Choice of bucket size can affect results:


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Principles ofGraphics Integrity (Tufte)

  • Proportional representation of numbers

  • Clear, detailed, thorough labeling

  • Show data variation, not design variation

  • Use deflated money units

  • Don’t have more dimensions than data has

  • Don’t quote data out of context


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Proportional Representationof Numbers

  • Maintain lie factor of 1.0

  • Use areas, not heights, with clip art

  • Avoiding “decorative” graphs will do wonders

    • Not too hard for most engineers!


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Clear, Detailed,Thorough Labeling

  • Goal is to defeat distortion and ambiguity

  • Write explanations on graphic itself

  • Label important events in the data


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Show Data Variation,Not Design Variation

  • Use one design for entire graphic

  • In papers, try to use one design for all graphs

  • Again, artistic license is big culprit


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Use Deflated Money Units

  • Often necessary to show money over time

    • Even in computer science

    • E.g., price/performance over time

    • Or expected future cost of a disk

  • Nominal dollars are meaningless

  • Derate by some standard inflation measure

    • That’s what the WWW is for!


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Don’t Have More Dimensions Than Data Has

  • This gets back to the Lie Factor

  • 1-D data (e.g., money) should occupy one dimension on the graph: not

  • Clip art is prohibited by this rule

    • But if you have to, use an area measure

$2.00

$1.00


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Don’t Quote DataOut of Context

  • Tufte’s example:



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Special-Purpose Charts

  • Tukey’s box plot

  • Histograms

  • Scatter plots

  • Gantt charts

  • Kiviat graphs


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Tukey’s Box Plot

  • Shows range, median, quartiles all in one:

  • Tufte can’t resist improvements:oror even

minimum

quartile

median

quartile

maximum


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Histograms

  • Tufte improves everything about them:


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Scatter Plots

  • Useful in statistical analysis

  • Also excellent for huge quantities of data

    • Can show patterns otherwise invisible


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Better Scatter Plots

  • Again, Tufte improves the standard

    • But it can be a pain with automated tools

  • Can use modified Tukey box plot for axes


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Gantt Charts

  • Shows relative duration of Boolean conditions

  • Arranged to make lines continuous

    • Each level after first follows FTTF pattern


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Kiviat Graphs

  • Also called “star charts” or “radar plots”

  • Useful for looking at balance between HB and LB metrics


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A Few Examples

  • A bad graph

  • Two good graphs




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A Superb Graph:DEC Traces



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