[OC] How to spot misleading charts? I would like to hear your opinion on the subject, also any tips design-wise?
Submitted by dark_o3 t3_zg7pck in dataisbeautiful
Reply to comment by dark_o3 in [OC] How to spot misleading charts? I would like to hear your opinion on the subject, also any tips design-wise? by dark_o3
Because that analogy just doesn't map to the situation here. There aren't certain plotting/graphing practices that are more likely to be associated with misleading data then they are with accurate data (except maybe not putting labels on your axis). You are making the assumption that if you see plots that do this, they are more likely to be misleading than accurate, but I don't think the data support that claim. I do everything on this list all the time in my job as an engineer, and I am doing it because it's the most accurate way to answer the questions that my data were collected to answer.
There are number of common practices which are used to mislead on purpose. The point is to show main tricks they use and to educate users to critically think about data thats presented to them.
Can you show me your data that these 'common practices' are being used to mislead more often than they are being used to accurate represent data?
I cannot support it with data nor did I claim they are more often on purpose. Sometimes it is just a bad design and different programmes have different default settings for labels and axis.
Okay, if you don't actually believe that these are practices that are more likely to be used to mislead than to accurately inform, then what is your justification for labeling them as misleading practices?
One of the most common misunderstandings I dealt with when I was doing STEM education with people reading graphs is when the data are presented non-linearly. If you present people with, for instance, a logarithmic graph it's much more likely they will get the wrong impression of the data. But I would never consider log graphs to be misleading. It seems to me like you are doing something analogous here.
These examples can be used to mislead and the purpose is to show to users how it can be done so the next time users sees truncated bar chart on TV, maybe they will think more carefuly before making judgment about visually represented data.
Okay, I said what I came here to say. There is nothing special about the examples you selected. If a user encounters, for instance, a bar chart that's been truncated not to start at zero, it's no more likely that this has been done for legitimate reasons than it is that it's been done for illegitimate ones. Similarly, it's just as likely that a bar chart which begins at zero had it's axis selected to mislead about the data as it is that is has it starting at zero to accurately represent the data. Flagging one of those options as potentially misleading is itself a potentially misleading statement.
If you feel like you need to get the last word in here, feel free. I think I've presented the best form of my argument so I am done now.
Actually, I will try and add one more thing to present more constructive criticism:
If you included an example of data being misrepresented by both options, I think you would solve the issue of misleading people into thinking certain plotting practices are intrinsically misleading. So, for instance, if you showed that data can be distorted by truncating a bar graph, but also that data can be distorted by NOT truncating a bar graph, I think you would make a far more valid argument about how to analyze graphical data skeptically.
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