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Home/ Questions/Q 7580137
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Editorial Team
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Editorial Team
Asked: May 30, 20262026-05-30T17:50:28+00:00 2026-05-30T17:50:28+00:00

(log n)^k = O(n)? For k greater or equal to 1. My professor presented

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(log n)^k = O(n)? For k greater or equal to 1.

My professor presented us with this statement in class, however I am not sure what it means for a function to a have a time complexity of O(n). Even stuff like n^2 = O(n^2), how can a function f(x) have a run time complexity?

As for the statement how does it equal O(n) rather than O((logn)^k)?

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  1. Editorial Team
    Editorial Team
    2026-05-30T17:50:29+00:00Added an answer on May 30, 2026 at 5:50 pm

    (log n)^k = O(n)?

    Yes. The definition of big-Oh is that a function f is in O(g(n)) if there exist positive constants N and c, such that for all n > N: f(n) <= c*g(n). In this case f(n) is (log n)^k and g(n) is n, so if we insert that into the definition we get: “there exist constants N and c, such that for all n > N: (log n)^k <= c*n“. This is true so (log n)^k is in O(n).

    how can a function f(x) have a run time complexity

    It doesn’t. Nothing about big-Oh notation is specific to run-time complexity. Big-Oh is a notation to classify the growth of functions. Often the functions we’re talking about measure the run-time of certain algorithms, but we can use big-Oh to talk about arbitrary functions.

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