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Basic Statistics: Discrete Data Vs. Continuous Data

You might say that discrete data isn’t very extraverted. It likes to sit by itself, isolated from the overly-complicated. Discrete data is a minimalist, and infinity is the enemy. Basically, anything that has a reasonably limited number of options is discrete.

The of sides on a dice? That’s discrete data. Available space on my flash drive? Discrete. Why? Because there’s only a certain number of available numbers that would work as a solution (e.g. there’s only 64 or less megabytes of storage on a 64 megabyte flash-drive).

Discrete data is the complete opposite of continuous data. Whereas discrete data is defined as something of reasonably limited possibilities, continuous data isn’t limited in possibility. Unlike discrete data, continuous data loves large amounts of possibilities and complicated muck (why do I seem so biased against continuous data? What has it ever done to me?). Either way, the differences are good to know.

Discrete Data: Reasonably limited in possibility.

Continuous data: Data that can take any value.

 

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