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fix typo #35

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2 changes: 1 addition & 1 deletion lessons/radix-sort.md
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Expand Up @@ -19,7 +19,7 @@ So what's the mechanism of doing this? Buckets! For base doing a positive intege

## Big O

So, this is way different than what we've been doing. So far we've just had `n` as a variable which represents how many items there are to sort. In radix sort (and other ones too) we have multiple variables. `n` is still important but now we have another variable in play here (usually called `k` or `w`. Let's go with `k` for our purposes.) `k` is going to represents the "maximum key length", or `d` as we referred to it as above. The more buckets we need, the larger the complexity. So intead of being O(n²) or O(n _ n), it ends up being O(n _ k). So is it better or worse than O(n log n) sorts? It depends! If you have a lot of numbers with lots of varied lengths that will bucket into a good distribution it can be very effective. If you numbers [1, 10, 100, 1000, 10000, 100000] etc it ends up being the worst sort. It ends up being O(n²) at that point.
So, this is way different than what we've been doing. So far we've just had `n` as a variable which represents how many items there are to sort. In radix sort (and other ones too) we have multiple variables. `n` is still important but now we have another variable in play here (usually called `k` or `w`. Let's go with `k` for our purposes.) `k` is going to represents the "maximum key length", or `d` as we referred to it as above. The more buckets we need, the larger the complexity. So instead of being O(n²) or O(n _ n), it ends up being O(n _ k). So is it better or worse than O(n log n) sorts? It depends! If you have a lot of numbers with lots of varied lengths that will bucket into a good distribution it can be very effective. If you numbers [1, 10, 100, 1000, 10000, 100000] etc it ends up being the worst sort. It ends up being O(n²) at that point.

What about the spatial complexity? It ends up being O(n + k) and this why radix sort is really only used in very specific circumstances: it's not great in terms of how much space it takes.

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