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<MIT's Introduction to Algorithms, Lecture 6: Order Statistics ⁄ >




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This is the fourth post in an article series about MIT's lecture course "Introduction to Algorithms." In this post I will review lecture six, which is on the topic of Order Statistics.

The problem of order statistics can be described as following. Given a set of N elements, find k-th smallest element in it. For example, the minimum of a set is the first order statistic (k = 1) and the maximum is the N-th order statistic (k = N).

Lecture six addresses the problem of selecting the k-th order statistic from a set of N distinct numbers.

The lecture begins with discussing the naive algorithm for finding k-th order statistic - sort the given set (or array) A of numbers and return k-th element A[k]. Running time of such algorithm at best is O(n·log(n)).



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http://www.catonmat.net/blog/mit-introduction-to-algorithms-part-four/




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