When and How to Use Log Scales in Think-Cell

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Chapters:
0:00 What is a log scale?
0:53 Why would you use log scales?
2:17 Capturing outliers
5:22 Underlying exponential data
7:13 A warning about log scales
Learn when and how to use logarithmic scales in Think-Cell.
💥 How do linear and log scales differ?
Linear scales increase by addition. For example: 1, 2, 3, 4, 5.
Log scales increase by multiplication. For example. 1, 10, 100, 1000, 10000.
Important: Log scales cannot have negative values.
💥 Why use a log scale?
There are two main reasons to use a log scale...
1) They allow a large range to be displayed, so that there isn't a large gap between typical data and outliers.
2) The underlying data is exponential and log scales allow you to better visualise detail across the entire dataset.
💥 Best practices
Don't use a log scale unless you have to, because they are not intuitive to read and you want the chart to be as easy to read as possible! And always note on the axis label that the scale is logarithmic.
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