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CMPT 880/890 Writing labs. Outline Presenting quantitative data in visual form Tables, charts, maps, graphs, and diagrams Information visualization.

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Presentation on theme: "CMPT 880/890 Writing labs. Outline Presenting quantitative data in visual form Tables, charts, maps, graphs, and diagrams Information visualization."— Presentation transcript:

1 CMPT 880/890 Writing labs

2 Outline Presenting quantitative data in visual form Tables, charts, maps, graphs, and diagrams Information visualization

3 Why present data? Data is evidence “Let the data speak for itself”

4 0.3048640.239580.8235920.2201720.1666010.217030.3790940.8887090.6042310.2897010.69145 0.712930.2471490.0200570.9758230.3852060.9201830.2348450.4231930.1297510.1065990.655337 0.5675280.3191040.9384420.4127720.3952830.2244060.5500020.8989190.2464670.4143230.549748 0.2919320.7177610.6810910.8631360.0153250.2052110.7081560.5367790.7183980.4972190.280734 0.2806630.4406270.4166950.8403440.8384190.1773350.2334690.2645620.6122070.6912070.900643 0.2861430.0684060.5759280.8877990.802490.5699980.2401590.8901580.7775560.3880250.442095 0.5214280.4477120.1911310.1749060.5909360.9058360.1418180.8523520.7383990.2507460.082781 0.5895540.5756690.6472590.2034870.2471810.6084160.069180.5582210.4557670.1853150.770355 0.9787790.3097470.3120570.8673480.2251820.9926440.3568660.1778840.383650.3546640.014401 0.0753150.9691360.5171580.3428620.897080.7976460.9883380.9159160.727290.8238940.521123 0.1967440.3867950.1242850.471880.7917310.2211970.8894460.2570130.3325550.9683940.869113 0.6828760.8087930.8103310.8110810.8841510.1683410.3954060.8240980.3300860.1161810.742156 0.6002070.6453690.7868290.8754530.2984350.0367720.1986260.6962890.2501920.7153130.862473 0.8942770.329210.725270.800720.5701460.7575580.1698240.6380690.4066140.5566120.199865 0.2312180.9003140.7139520.8229150.5120350.9886350.4207750.8374810.2054480.9406550.853948 0.7588240.6242050.1381290.0195010.9651860.4729780.6111440.9657010.004930.2405620.617086 0.2013670.735260.6389960.5574450.6088960.5168240.9382810.2914820.3517850.6828830.859275 0.0081010.0014180.8069070.0238950.9229670.7800370.5328170.8973870.7529640.2453080.868724 0.3166870.0851280.5582960.6299620.5188760.2065190.4772390.73390.6590470.9734490.415621 0.8374320.2483660.0936850.3044590.1037780.4222560.2841790.2596660.0001850.1905510.760345 0.8325360.2596590.3967410.0880270.2542710.7617750.2304210.9731540.108310.8365710.418838 0.9778040.0408270.9962750.9486930.2083620.4444560.4804830.8624320.6570240.0350520.711469 0.7722970.3245860.2408940.9609260.7900590.9613450.016020.5450910.8021290.090030.671506 0.7603260.2313810.2097540.2146680.196840.9223510.5709110.2205430.5053070.2508860.593244 0.3493020.6709050.0916170.6025750.2906170.0132530.6183240.9412950.9364340.2423220.339894 0.8800040.3394710.6736880.0834080.9875610.7147780.0137140.3024570.9446770.288020.677895 0.8562140.3044820.0928970.7619280.7578040.4980510.6191150.2980620.0650460.7302030.04564 0.7560570.9999270.5405080.0269110.8162530.1099780.5016790.0611640.8608260.2839880.116396 0.1881620.4260210.9744750.8032140.6336590.665710.8991550.1054770.5410410.4651410.931354 0.4431240.2235740.752410.6007030.0756070.9167270.497120.5435590.7631930.5865420.682322

5 Why present data? Data is evidence “Let the data speak for itself your argument” Remember: you are making a claim how will your evidence aid your argument? what are you trying to show? What kind of visual presentation will convey the necessary information to your readers?

6 Displaying quantitative information Table or chart? Tables are useful when: it is important to see individual values it is important to compare individual values precision is important there is only a small amount of data Charts are useful when: the message can be seen in the shape of the data e.g.: trends, relationships, exceptions

7 Guiding principles All of the data you present in a chart or table should be relevant to your argument The data should stand out clearly without distraction Should you make your charts and tables fancy? No.

8 Designing tables Do you need a table? Data can be presented inline in your text “In 1996, on average, men earned $32,144 a year, and women $23,710, a difference of $8,434.” This takes up much less space than a table! Use a table only when the numbers make the paragraph confusing or clumsy

9 Designing tables What conclusion(s) do you want the reader to draw? Too much information will obscure the comparisons What rows and columns? What order for the rows and columns? How many rows and columns? heuristics: 7x7 maximum; 100 items maximum

10 Designing tables Formatting guidelines: Rows and columns should be clearly labeled White space instead of lines between columns Lines between rows for grouping Use appropriate precision Fewer significant digits = easier to read Do not repeat symbols such as % or $ within the table Include them in the row or column titles. Should you make the table fancy? No.

11 0.3048640.239580.8235920.220172 0.712930.2471490.0200570.975823 0.5675280.3191040.9384420.412772 0.2919320.7177610.6810910.863136 0.2806630.4406270.4166950.840344 JuneJulyAugustAverage EEE0.970.560.790.77 HP0.610.760.520.63 Apple0.700.390.290.46 Lenovo0.280.610.180.36 Dell0.700.010.330.35 JuneJulyAugustAverage EEE0.970.560.790.77 HP0.610.760.520.63 Apple0.700.390.290.46 Lenovo0.280.610.180.36 Dell0.700.010.330.35





16 From tables to charts

17 Charts Less precise than tables, but greater impact Use a chart when the message can be seen in the shape of the data trends, relationships, exceptions

18 Tables may not tell the story best N: 11 mean Xs : 9.0 mean Ys : 7.5 standard error of slope estimate: 0.1 sum of squares: 110.0 regression sum of squares: 27.5 residual sum of squares of Y: 13.8 correlation coefficient: 0.8 r squared: 0.7 regression line: Y=3+0.5X

19 Visual representation

20 Do I deserve a tax break?


22 Types of charts Hundreds of types! Most of the time, use the simple types: bar chart line chart histogram scatterplot pie chart

23 Types of attribute data Nominal data Category data that can only be compared for equality e.g. apple, orange Ordinal data Ordering and ranking based on e.g. restaurant ratings Interval data Ordering and arithmetic possible but no natural zero e.g. temperatures, dates Ratio data Ordered, natural zero e.g. height, weight, age, length

24 Ease of visual comparison


26 Bar charts Use a bar graph to illustrate differences between specific point values Don’t use a bar graph to illustrate trends Use a bar graph for categorical data Arrange categories (the X axis) to reinforce your story

27 Bar charts

28 Use a horizontal bar graph if the labels are too long to fit under a vertical bar graph Arrange and mark corresponding bars in the same way


30 Bar charts: isotype

31 Line charts Use a line graph if the X axis has a continuous scale e.g., time, distance, temperature lines allow interpolation Use a line graph to display trends

32 Line charts Don’t use a line graph to show point values

33 Line charts Use a line graph to display interactions

34 Line charts Formatting guidelines: X and Y axes must be clearly identifiable and appropriately labeled Ensure that points and lines are discriminable If lines connect points, make sure the points are visible Use a grid when precise values are important


36 Scatterplots Use a scatterplot to convey an overall impression of the relationship between two variables More than two becomes confusing

37 Scatterplots Scatterplots are not good for showing precise values Grids not usually used

38 Scatterplots Fit a line through a scatterplot to show how closely two variables are related

39 Scatterplots What if you want to show more attributes? Change the appearance of an individual mark Visual variables


41 Multi-dimensional scatterplot

42 Pie charts Use a pie to convey approximate relative amounts Label wedges if precise values are important Arrange wedges in order of size unless the data demands a different organization

43 Which is the largest?

44 Clockwise ordering

45 Lie factors Are you misleading the reader?

46 Lie factors Height or area? (or volume?)

47 Lie factors Height or area? (or volume?)


49 Lie factors Scale on Y axis

50 Lie factors Scale on Y axis

51 Lie factors Scale on Y axis

52 Lie factors Scale on Y axis

53 Lie factors Show appropriate context

54 Lie factors Switched X and Y axes

55 Chartjunk Remember that your goal is to convey meaning to your reader in support of your argument Chartjunk is any extra ink that does not do this

56 Chartjunk


58 3D effects: chartjunk




62 “The worst graphic ever made”

63 Analyse the following charts

64 Maintenance cost per year




68 Don’t be lazy

69 Maps

70 Use a map when your data has location information X and Y are now used for location

71 Election forecast

72 Cholera epidemic 1854

73 Napoleon's march on Moscow

74 Exercise

75 CityClimateHousingHlthCareCrimeTranspEducArtsRecreatEconLongLatPop Abilene52162002379234031275799614057633-99.68932.559110932 Akron5758138165688648832438556426324350-81.51841.085660328 Albany4687339618970253125602378595250-84.15831.575112402 Albany4767908143161068833399465516175864-73.798342.7327835880 Albuquerque65983931853148365583026449626125727-106.6535.083419700 Alexandria52058196407272444297233410185254-92.45331.302135282 Allentown559828862151428813144233311175097-75.440540.6155635481 Alton537648796570649752945148712805795-90.161538.794268229 Altoona56161914323994246277825612104230-78.39540.515136621 Amarillo6096546669107349022852123511096241-101.84935.383173699 Where to live in the U.S.?

76 Climate

77 Crime vs. climate

78 Multiple attributes – radar plot

79 Map

80 Going further If these basic types of charts don’t fit your need, there are many resources to help you find out more Edward Tufte, The Visual Display of Quantitative Information Stephen Kosslyn, Elements of graph design Robert Spence, Information Visualization Tools:

81 Going further

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