# F(n) = \Left\lceil \Frac{n}{4}\right\rceil^2  URL:: https://brilliant.org/courses/computer-science-algorithms/the-speed-of-algorithms-2/more-big-o/5/ Author:: brilliant.org ## Highlights > Saying that f(n)=n−1f(n) = n - 1f(n)=n−1 is in O(n3)O(n^3)O(n3) is true, and as you'll see in the next lesson, the math works out. But that's also **confusing and unhelpful**. The most informative statement would be to say that you know the algorithm to be in O(n)O(n)O(n). > Informally, when a computer scientist says that an algorithm is in O(n2),O(n^2),O(n2), she means that she knows the algorithm runs in quadratic time, and that that is the **best** description of running time she knows how to give for the algorithm. ([View Highlight](https://read.readwise.io/read/01ga7fgmx1h7hb62abk6hyb604)) --- Title: F(n) = \Left\lceil \Frac{n}{4}\right\rceil^2 Author: brilliant.org Tags: readwise, articles date: 2024-01-30 --- # F(n) = \Left\lceil \Frac{n}{4}\right\rceil^2  URL:: https://brilliant.org/courses/computer-science-algorithms/the-speed-of-algorithms-2/more-big-o/5/ Author:: brilliant.org ## AI-Generated Summary Not all algorithms have a runtime cost that's a nice polynomial function of n. For instance, you might have an array algorithm that runs in k2steps on arrays of length n=4k. ## Highlights > Saying that f(n)=n−1f(n) = n - 1f(n)=n−1 is in O(n3)O(n^3)O(n3) is true, and as you'll see in the next lesson, the math works out. But that's also **confusing and unhelpful**. The most informative statement would be to say that you know the algorithm to be in O(n)O(n)O(n). > Informally, when a computer scientist says that an algorithm is in O(n2),O(n^2),O(n2), she means that she knows the algorithm runs in quadratic time, and that that is the **best** description of running time she knows how to give for the algorithm. ([View Highlight](https://read.readwise.io/read/01ga7fgmx1h7hb62abk6hyb604))