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+# Intuition
+
+If you're not familiar with probabilistic data structures then getting an intuition for how this data structure works
+using a real world example might be helpful.
+
+Imagine you wanted to count how many raindrops fall from the sky and landing in certain area, let's say one square meter.
+A single raindrop will fall randomly hitting the ground in the area you wish to analyze. Trying to count every single drop
+that hits the ground would be very difficult, there are simply far too many.
+
+Perhaps you can estimate the number of raindrops?
+
+Instead of counting each and every drop of rain you could instead lay out a grid of buckets and then count how many buckets
+have *any* raindrops in them at all. For this thought experiment we're not considering how _much_ water is in them, only if
+there is a non-zero amount of water. Uniformly sized buckets might work ok for a small shower, but you'd quickly run
+into an issue where most of your buckets have some amount rain in them. Because of this, you would not be able to differentiate between a gentle shower and a downpour; either way most of the buckets have _some_ water in them.
+
+By varying the size of the buckets you reduce the probability that a raindrop will land in the smaller ones. You can
+then estimate the number of droplets by adding up the probabilities that a given bucket has a raindrop in it. Smaller
+ones are much less likely to have a droplet in so if you've got a lot of smaller buckets with drop lets in, that would imply
+that there was a lot of rain. If those buckets are mostly dry, then it would imply that there was only a small amount
+of drizzle. You still need a wide range of bucket sizes to be able to tell the difference between having no rain and a small
+amount of rain.
+
+You can estimate the difference in the amount of rain fall on two areas by counting the number of buckets where the matching
+bucket size has rain in it in one area but not the other.
+
+This data structure works in a similar way. Items are hashed to produce a "random" number which we assign to a bucket. The
+bucket "sizes" are arranged to follow a geometric distribution to allow us to calculate an estimate of the number of items
+using well known formulas.
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