randomized selection algorithm

The randomized selection algorithm efficiently finds the k-th smallest element in an unsorted list by using a random approach. It works similarly to quicksort: it picks a random element as a pivot and partitions the list into elements smaller and larger than this pivot. Depending on the position of the pivot, it then recursively searches only in the relevant part of the list. Because the pivot choice is random, the algorithm often performs well on average, quickly narrowing down to the desired element without fully sorting the list. This makes it an effective method for large datasets where order statistics are needed.