1. Pitfalls and misuses of statistics and graphs
Data Visualisation
Pitfalls and misuses of statistics and graphs
CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION
Iraj Namdarian
Luxembourg – 22/05/2015

2. Session overview Data Visualisation
Pitfalls and misuses of statistics and graphs
Use and Abuse of Statistics and Figures
Problems with interpretation
Misleading graph methods

3. When clarity makes way for pretty
Graphics are a great way of communicating data, but a chart for a chart’s sake is not always a good idea. Here are some common ways that charts confuse rather than elucidate.

4. When clarity makes way for pretty
This chart compares the return on investment for two mutual funds in successive years. It would appear that Fund B outperformed Fund A slightly in three years.

5. When clarity makes way for pretty
Here is the same data in more conventional but less pretty format. Now it is clear that Fund A outperformed Fund B in 3 out of 4 years, not the other way around.

6. Use and Abuse of Statistics and Figures
Three dimensional depictions of data are hard to perceive clearly, and the general rule of thumb is to only use as many dimensions as the data one is trying to show.

7. Misleading graph
In statistics, a misleading graph, also known as a distorted graph, is graph which misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it. Graphs may be misleading through being excessively complex or poorly constructed. Even when constructed to accurately display the characteristics of their data, graphs can be subject to different interpretation.

8. Misleading graph
Misleading graphs may be created intentionally to hinder the proper interpretation of data or accidentally due to unfamiliarity with graphing software, misinterpretation of data, or because data cannot be accurately conveyed. Misleading graphs are often used in false advertising. 

9. Misleading graph methods
Excessive usage The use of graphs where they are not needed can lead to unnecessary confusion/interpretation. Generally, the more explanation a graph needs, the less the graph itself is needed. Graphs do not always convey information better than tables.

10. Misleading graph methods
Biased labelling The use of biased or loaded words in the graph's title, axis labels, or caption may inappropriately prime the reader

11. Misleading graph methods
Pie chart:
Comparing pie charts of different sizes could be misleading as people cannot accurately read the comparative area of circles.
The usage of thin slices which are hard to discern may be difficult to interpret.

12. Misleading graph methods
Pie chart:
The usage of percentages as labels on a pie chart can be misleading when the sample size is small.
Making a pie chart 3D or adding a slant will make interpretation difficult due distorted effect of perspective. Bar-charted pie graphs in which the height of the slices is varied may confuse the reader.

13. Misleading graph methods
3D Pie chart slice perspective A perspective (3D) pie chart is used to give the chart a 3D look. Often used for aesthetic reasons, the third dimension does not improve the reading of the data; on the contrary, these plots are difficult to interpret because of the distorted effect of perspective associated with the third dimension.

14. Misleading graph methods
3D Pie chart slice perspective The use of superfluous dimensions not used to display the data of interest is discouraged for charts in general, not only for pie charts. In a 3D pie chart, the slices that are closer to the reader appear to be larger than those in the back due to the angle at which they're presented.

15. Misleading graph methods
In the misleading pie chart, Item C appears to be at least as large as Item A, whereas in actuality, it is less than half as large.

16. Misleading graph methods
Improper scaling When using pictogram in bar graphs, they should not be scaled uniformly as this creates a perceptually misleading comparison. The area of the pictogram is interpreted instead of only its height or width. This causes the scaling to make the difference appear to be squared.

17. Misleading graph methods
Note how in the improperly scaled pictogram bar graph, the image for B is actually 9 times as large as A.

18. Misleading graph methods
Improper scaling The effect of improper scaling of pictogram is further exemplified when the pictogram has 3 dimensions, in which case the effect is cubed. Additionally, an improperly scaled pictogram may leave the reader with the sense that the item itself has actually changed in size.

19. Misleading graph methods
Assuming the pictures represent equivalent quantities, note how in the misleading graph, there appears to be more bananas because the bananas occupy the most area and are furthest to the right.

20. Misleading graph methods
Truncated graph
A truncated graph (also known as a torn graph) has a y-axis that does not start at 0. These graphs can create the impression of important change where there is relatively little change.
Truncated graphs are useful in illustrating small differences. Graphs may also be truncated to save space. Commercial software such as MS Excel will tend to truncate graphs by default if the values are all within a narrow range.

21. Misleading graph methods
Note that both of these graphs display identical data; however, in the truncated bar graph on the left,
the data appear to show significant differences, whereas in the regular bar graph on the right, these differences are hardly visible.

22. Misleading graph methods
Axis changes
Changing the y-axis maximum affects how the graph appears. A higher maximum will cause the graph to appear to have less-volatility, less-growth and a less steep line than a lower maximum.

23. Misleading graph methods
Axis changes
Changing the ratio of a graph's dimensions will affect how the graph appears.

24. Misleading graph methods
No scale: The scales of a graph are often used to exaggerate or minimize differences
Note the lack of a starting value for the y-axis, which makes it unclear if the graph is truncated. Additionally, note the lack of tick marks which prevents the reader from determining if the graph bars are properly scaled. Without a scale, the visual differences between the bars can be easily manipulated.

25. Misleading graph methods
Omitting data:
Graphs created with omitted data remove information from which to base a conclusion.
Note how in the scatter plot with missing categories on the left, the growth appears to be more linear with less variation.

26. Misleading graph methods
Improper extraction
Graphs based on other graphs should be representative in their presentation. Extraction has valid uses when searching for anomalies.
Note how the extracted graph does not accurately represent the original graph.

27. Misleading graph methods
The use of a superfluous third dimension which does not contain information is strongly discouraged as it may confuse the reader.

28. Misleading graph methods
Complexity
Graphs are designed to allow for easier interpretation of statistical data. However, graphs with excessive complexity can obfuscate the data and make interpretation difficult.
Poor construction
Poorly constructed graphs can make data difficult to discern and thus interpret.
Improper intervals/units
The intervals and units used in a graph may be manipulated to create or mitigate the expression of change.

29. Thank you
CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION