4 ms·

In all honesty, I know what I'm looking at and I still find it hard to understand by comparison. It's also poor graphing. Graphs should have a purpose and comm

In all honesty, I know what I'm looking at and I still find it hard to understand by comparison. It's also poor graphing. Graphs should have a purpose and communicate information as clearly as possible. Scales and units should be chosen to most effectively convey information. Logarithmic scales are a poor choice for the information being displayed.

KarlKemp 6y ago
The logarithm is appropriate because disease transmission is an exponential process. For a given set of parameters (of measures such as social distancing, mask wearing, weather, etc.) new infections will not rise by some specific, absolute number. Rather, similar environments result in similar rates of new infections as a percentage of existing, active infections.
- grawprog 6y ago
  But that's not what the graphs are showing. The graphs are showing continuous infections over February, March and April. Those are not unknown future times. Those are past times with existent data. There's no reason not to represent those data as clearly as possible. Which a logarithmic scale does not. Again graphs should serve one purpose. The purpose of those graphs is clearly, by the axis labels, supposed to display continuous deaths over a set period of time. The linearly scaled graph displays this clearly, the logarithmic one does not. If the x-axis displayed into some future time, yes I'd agree a logarithmic scale may be more appropriate. But that would be displaying a graph of predictions at that point, which is something totally different than the two example graphs are showing.
  - plerpin 6y ago
    Simply asserting that graphs should communicate one purpose does not make it so. Multiple audiences require multiple techniques for visualization and analysis. A logarithmic scale communicates the characteristics of an exponential curve better than a linear scale.

KarlKemp 6y ago

The logarithm is appropriate because disease transmission is an exponential process. For a given set of parameters (of measures such as social distancing, mask wearing, weather, etc.) new infections will not rise by some specific, absolute number. Rather, similar environments result in similar rates of new infections as a percentage of existing, active infections.

grawprog 6y ago
But that's not what the graphs are showing. The graphs are showing continuous infections over February, March and April. Those are not unknown future times. Those are past times with existent data. There's no reason not to represent those data as clearly as possible. Which a logarithmic scale does not. Again graphs should serve one purpose. The purpose of those graphs is clearly, by the axis labels, supposed to display continuous deaths over a set period of time. The linearly scaled graph displays this clearly, the logarithmic one does not. If the x-axis displayed into some future time, yes I'd agree a logarithmic scale may be more appropriate. But that would be displaying a graph of predictions at that point, which is something totally different than the two example graphs are showing.
- plerpin 6y ago
  Simply asserting that graphs should communicate one purpose does not make it so. Multiple audiences require multiple techniques for visualization and analysis. A logarithmic scale communicates the characteristics of an exponential curve better than a linear scale.