Also, even though quick sort is the fastest with mostly random data sets, If you have a data set that is already mostly sorted (for example you only need to switch two values), It can actually be one of the least efficient sorting methods. It's a matter of knowing what kind of data you're working with and picking the right method.

True. Though if you have a relatively small number of anything to sort (like under 100), you can be pretty confident that just about any non-laughable algorithm will sort it pretty quickly, so you don't need to belabor the matter unduly. Just do an insertion sort, it's impossible to get it wrong.

You should try MemeSort!

MemSort takes the largest and smallest values and the mean value, then does the following:

1.) Erases all data not the extremes and the mean.
2.) Fakes new data that fits between the extremes and the mean.
3.) Displays a preproduced jpeg of the sorted data regardless of what goes in or who uses it for what. I call it Whatever In This Image Out (WITIO).

MemeSort is presently used at the Vatican to prove the existence of God.

I can't make these jokes often and to too many people, so I am grateful.

We'd be the poorer without you. And our data would be less replicatable.

An average of n! efforts, probably.

Best case: 1 iteration
Average case: n! iterations
Worst case: never