In a previous post describing a simple approach to de-seasonalizing your data, I covered how marketers can examine, at a rough level, the impact of seasonality on metrics. Obviously, your data science team would be looking at this data in greater depth and, to be sure, a more precise calculation of seasonality is a far more complex undertaking. The basic thought process, however, is a valuable learning for business people.

Today, let’s try this on another topic: using a boxplot to get a general overview of the spread of your data without using “capital S” Statistics, and, again at a rough level, making smarter “guestimates” of outcomes.

What is a boxplot?

A boxplot looks something like this:


It has a central box with a divider inside, and two “whiskers” going out each side.

Read this entire article over at my column

Thinking Inside The Boxplot

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