I've been posting a lot of philosophical geekery lately, so I'll balance that today with some math geekery. Today's math term is *equivalence class*. The basic idea is simple: if you have a big set of things, you can reduce it to a smaller set of things, each of which is a subset, or "class", of those things that are “equivalent” in some well-defined way.

Here's an example: how many five-card poker hands are there? Well we can pick any card from a 52-card deck, then pick a second card from the 51 remaining, and so on five times. This gives us 52×51×50×49×48 hands, or 311,875,200. Those 300 million hands include A♥4♦A♣9♥4♣ and also 4♣9♥A♣A♥4♦, so we can immediately reduce that by a factor of 120 by noting that poker rules don't care what order the cards are in. So we collect all those together and reduce our number to 2,598,960.

But we can go further still. That 2.5 million counts our two hands above (along with other combinations like 9♥4♦A♥4♣A♣) as equivalent, but it counts separately the hand A♠A♥4♥4♦9♠, which is the “same” hand in the sense of being identically valued—it is “two pair, aces and fours, nine kicker”, just like the first two. So how many poker hands are there, only counting those that are actually of different value in the game? As it turns out, only 7,462. Number one at the top of that list of 7,462 is simply “royal flush”, which accounts for four of our 2.5 million hands, and 480 of our 300 million. Number 2 is “king high straight flush”, and so on down to number 7,462 which is “no pair, 7-5-4-3-2” (which accounts for 1,020 of our 2.5 million, or 122,400 of our 300 million).

Notice a major difference between our two reduction operations: in the first case, we reduced the big set into subsets that were all the same size. Each of our 2.5 million hands contains exactly 120 of our 300 million—that's the number of different ways you can arrange 5 cards. As a consequence of this, the probability of each of those 2.5 million hands is exactly the same, just as is the probability of each of the 300 million. The 7,462 sets, however, are of different sizes. There are hundreds of times as many ways to get 7-5-4-3-2 as there are to get a royal flush, so the probability of each is different.

One common application of equivalence classes is in computer science: sometimes you need to do something to a very large set of inputs, and you can simplify and speed up the operation by reducing them to a smaller set. If you ask Google for pages about “poker”, not only would you expect it to return pages that mention “Poker” and “POKER”, but Google would save time and disk space by indexing those only once.

This can be applied to life as well. Perhaps there is a large set of things you'd like to improve about your life in some way. If you can group them by things that might have a similar cause or similar solutions, not only will you reduce the number of things to think about, you might notice that some groups are much larger than others, giving you guidance about what to focus on.