When we take pictures with a digital camera or smartphone, what the device really does is capture information in the form of binary code. At the most basic level, our precious photos are really just a bunch of 1s and 0s, but if we were to look at them that way, they'd be pretty unexciting.

In its raw state, all that information the camera records is worthless. The 1s and 0s need to be converted into pictures before we can actually see what we’ve photographed.

We encounter a similar situation when we try to use statistical distributions and parameters to describe data. There’s important information there, but it can seem like a bunch of meaningless numbers without an illustration that makes them easier to interpret.

For instance, if you have data that follow a gamma distribution with a scale of 8 and a shape of 7, what does that really mean? If the distribution shifts to a shape of 10, is that good or bad? And even if you understand it, how easy would it be explain to people who are more interested in outcomes than statistics?

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