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Introduction to Graphical Presentation

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Clip Art. In or out? Filled 'Walls' Borders and. Fills Galore. Unintentional. Heavy or Double Lines ... heights, with clip art. Avoiding 'decorative' graphs ... – PowerPoint PPT presentation

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Title: Introduction to Graphical Presentation


1
Introduction toGraphical Presentation
  • Andy Wang
  • CIS 5930-03
  • Computer Systems
  • Performance Analysis

2
The Art of Graphical Presentation
  • Reference Works
  • Types of Variables
  • Guidelines for Good Graphics Charts
  • Common Mistakes in Graphics
  • Pictorial Games
  • Special-Purpose Charts

3
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

4
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)

5
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

6
Guidelines for Good Graphics Charts
  • Principles of graphical excellence
  • Principles of good graphics
  • Specific hints for specific situations
  • Aesthetics
  • Friendliness

7
Principlesof Graphical Excellence
  • Graphical excellence is the well-designed
    presentation of interesting data
  • Substance
  • Statistics
  • Design

8
Graphical Excellence (2)
  • Complex ideas get communicated with
  • Clarity
  • Precision
  • Efficiency

9
Graphical Excellence (3)
  • Viewer gets
  • Greatest number of ideas
  • In the shortest time
  • With the least ink
  • In the smallest space

10
Graphical Excellence (4)
  • Is nearly always multivariate
  • Requires telling truth about data

11
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

12
Above All ElseShow the Data
13
Above All ElseShow the Data
14
Maximize theData-Ink Ratio
15
Maximize theData-Ink Ratio
16
Erase Non-Data Ink
17
Erase Non-Data Ink
North
West
East
18
Erase Redundant Data Ink
North
West
East
19
Erase Redundant Data Ink
North
West
East
20
Revise and Edit
21
Revise and Edit
22
Revise and Edit
23
Revise and Edit
24
Revise and Edit
25
Revise and Edit
26
Revise and Edit
27
Specific Things to Do
  • Give information the reader needs
  • Limit complexity and confusion
  • Have a point
  • Show statistics graphically
  • Dont always use graphics
  • Discuss it in the text

28
Give Informationthe Reader Needs
  • Show informative axes
  • Use axes to indicate range
  • Label things fully and intelligently
  • Highlight important points on the graph

29
Giving Informationthe Reader Needs
30
Giving Informationthe Reader Needs
31
Limit Complexityand Confusion
  • Not too many curves
  • Single scale for all curves
  • No extra curves
  • No pointless decoration (ducks)

32
Limiting Complexityand Confusion
33
Limiting Complexityand Confusion
34
Have a Point
  • Graphs should add information not otherwise
    available to reader
  • Dont plot data just because you collected it
  • Know what youre trying to show, and make sure
    the graph shows it

35
Having a Point
  • Sales were up 15 this quarter

36
Having a Point
37
Having a Point
38
Having a Point
39
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

40
Dont 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

41
Text Would HaveBeen Better
42
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

43
Aesthetics
  • Not everyone is an artist
  • But figures should be visually pleasing
  • Elegance is found in
  • Simplicity of design
  • Complexity of data

44
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

45
Use AppropriateFormat and Design
  • Dont 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

46
Using Text as a Graphic
About a year ago, eight forecasters were asked
for their predictions on some key economic
indicators. Heres how the forecasts stack up
against the probable 1978 results (shown in the
black panel).
(New York Times, Jan. 2, 1979)
47
The Stem-and-Leaf Plot
  • From Tukey, via Tufte, heights of volcanoes in
    feet 098766562 197719630 299987766544422211
    009850 3876655412099551426 4999884433192943336
    1107 597666666554422210097731 6898665441077761
    065 798855431100652108073 8653322122937

48
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

49
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

50
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

51
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

52
Better Proportion
  • Sales in North and West districts were steady
    through all quarters
  • East sales varied widely, significantly
    outperforming other districts in third quarter

53
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, dont use elaborate shadings and a
    complex legend
  • Avoid red/green distinctions
  • Use clean, serif fonts in mixed case

54
An Unfriendly Graph
55
A Friendly Version
56
Even Friendlier
57
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 thats because we hit a CPU bottleneck

58
Showing a StoryAbout the Data
59
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

60
Avoid Decorationand Chartjunk
  • Powerpoint, etc. make chartjunk easy
  • Avoid clip art, automatic backgrounds, etc.
  • Remember data is the story
  • Statistics arent boring
  • Uninterested readers arent drawn by cartoons
  • Interested readers are distracted
  • Does removing it change message?
  • If not, leave it out

61
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
62
Common Mistakesin Graphics
  • Excess information
  • Multiple scales
  • Using symbols in place of text
  • Poor scales
  • Using lines incorrectly

63
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, dont cram things in

64
Way Too Much Information
65
Whats ImportantAbout That Chart?
  • Times for cp and rcp rise with number of replicas
  • Most other benchmarks are near constant
  • Exactly constant for rm

66
The Right Amountof Information
67
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 doesnt exist

68
Some Especially Bad Multiple Scales
69
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...

70
Its All Greek To Me...
71
Explanation is Easy
72
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 dont lie or cheat
  • Sometimes trimming off high ends makes things
    clearer
  • Brings out low-end detail

73
Nonzero Origins(Chosen by Microsoft)
74
Proper Origins
75
A Poor Axis Range
76
A Logarithmic Range
77
A Truncated Range
78
Using Lines Incorrectly
  • Dont connect points unless interpolation is
    meaningful
  • Dont smooth lines that are based on samples
  • Exception fitted non-linear curves

79
Incorrect Line Usage
80
Pictorial Games
  • Non-zero origins and broken scales
  • Double-whammy graphs
  • Omitting confidence intervals
  • Scaling by height, not area
  • Poor histogram cell size

81
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)

82
Non-Zero Origins
83
The Three-Quarters Rule
  • Highest point should be 3/4 of scale or more

84
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

85
OmittingConfidence Intervals
  • Statistical data is inherently fuzzy
  • But means appear precise
  • Giving confidence intervals can make it clear
    theres no real difference
  • So liars and fools leave them out

86
Graph WithoutConfidence Intervals
87
Graph WithConfidence Intervals
88
Scaling by HeightInstead of Area
  • Clip art is popular with illustrators

Women in the Workforce
89
The Troublewith Height Scaling
  • Previous graph had heights of 21
  • But people perceive areas, not heights
  • So areas should be whats 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)

90
Scaling by Area
  • Same graph with 21 area

Women in the Workforce
91
Poor Histogram Cell Size
  • Picking bucket size is always problem
  • Prefer 5 or more observations per bucket
  • Choice of bucket size can affect results

92
Principles ofGraphics Integrity (Tufte)
  • Proportional representation of numbers
  • Clear, detailed, thorough labeling
  • Show data variation, not design variation
  • Use deflated money units
  • Dont have more dimensions than data has
  • Dont quote data out of context

93
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!

94
Clear, Detailed,Thorough Labeling
  • Goal is to defeat distortion and ambiguity
  • Write explanations on graphic itself
  • Label important events in the data

95
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

96
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
  • Thats what the WWW is for!

97
Dont 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
98
Dont Quote DataOut of Context
  • Tuftes example

99
The Same Data in Context
100
Special-Purpose Charts
  • Tukeys box plot
  • Histograms
  • Scatter plots
  • Gantt charts
  • Kiviat graphs

101
Tukeys Box Plot
  • Shows range, median, quartiles all in one
  • Tufte cant resist improvementsoror even

minimum
maximum
quartile
quartile
median
102
Histograms
  • Tufte improves everything about them

103
Scatter Plots
  • Useful in statistical analysis
  • Also excellent for huge quantities of data
  • Can show patterns otherwise invisible

104
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

105
Gantt Charts
  • Shows relative duration of Boolean conditions
  • Arranged to make lines continuous
  • Each level after first follows FTTF pattern

106
Kiviat Graphs
  • Also called star charts or radar plots
  • Useful for looking at balance between HB and LB
    metrics

107
A Few Examples
  • A bad graph
  • Two good graphs

108
A Very Bad Graph
109
A Good Graph Sunspots
110
A Superb GraphDEC Traces
111
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