Ted's Tutorials 001 - Box Plot with outliers

Hello everybody, welcome to Ted’s Tutorials, where I will be weekly releasing some tips and tricks I’ve learnt or found useful throughout my experience with a range of different software. 

To start off the very first tutorial, we will be looking at how to create a boxplot with outliers! Boxplots, also referred to as Box-and-whisker plots, are a great way to quickly understand the distribution of data. They tell you very quickly: 

  • The min, median and max value to show you how spread out or diverse your dataset is
  • If you have any outliers in the data…they will be beyond the "whiskers"
  • Distributions across categories, useful for comparing across multiple groups side-by-side

Examples of when they can be used effectively:

  • Customer purchase amounts: detecting big spenders vs typical buyers
  • Employee salaries across departments: identifying pay gaps
  • Website load times across regions: finding anomalies
  • Patient recovery times by treatment type: evaluating effectiveness

When not to use:

  • If you have very few data points (<~15) - the boxplot will become misleading
  • If your audience isn't familiar with terms like median, quartiles, or outliers, they might misinterpret the boxplot - People often assume the top of the box is the maximum (it’s not!)

Watch below to see how to set up a boxplot on Tableau!!

Author:
Ted Evans
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