This post offers reasons for using logarithmic scales, also called log scales, on charts and graphs. It explains when logarithmic graphs with base 2 are preferred to logarithmic graphs with base 10.

Logarithmic price scales tend to show less severe price increases or decreases than linear price scales. For example, if an asset price has collapsed from $100.00 to $10.00, the distance between ...

The second finding, however, is the key weakness of a log chart: people have a hard time interpreting the scale. In the log chart, the final dot looks like it’s at around 60-70,000 deaths or so.

Graphs that are not drawn to scale mislead the reader. This post shows another example of a graph where the visual representation of the numbers is not proportional to the numbers themselves.

But sharp-eyed observers will note that the chart is in log scale, not linear scale. In a regular linear scale graph -- the type of scale everyone is used to seeing on a daily basis in everything ...

The data look very different when plotted on what is called a logarithmic scale. In a typical graph, values on the (vertical) y-axis are plotted linearly: 1, 2, 3, and so on, or 10, 20, 30, or the ...