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Question
In algorithms, if T, for time complexity of an algorithm (calculated as number of steps/operations), in relations to problem input size, n, is: 𝑇 (𝑛) = 5𝑛^2 + 27𝑛 + 1005.
Why do we then say the big-O time complexity is simply O(n^2)?
Because in Big-O (O for order magnitude), we only care about really large input sizes. And as n gets really big, the 5 in the 5n^2, and also the entire 27n+1005 parts of the time complexity become insignificant, compared to just the n^2 part.

Question
In algorithms, if T, for time complexity of an algorithm (calculated as number of steps/operations), in relations to problem input size, n, is: 𝑇 (𝑛) = 5𝑛^2 + 27𝑛 + 1005.
Why do we then say the big-O time complexity is simply O(n^2)?
?

Question
In algorithms, if T, for time complexity of an algorithm (calculated as number of steps/operations), in relations to problem input size, n, is: 𝑇 (𝑛) = 5𝑛^2 + 27𝑛 + 1005.
Why do we then say the big-O time complexity is simply O(n^2)?
Because in Big-O (O for order magnitude), we only care about really large input sizes. And as n gets really big, the 5 in the 5n^2, and also the entire 27n+1005 parts of the time complexity become insignificant, compared to just the n^2 part.
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#### pdf

owner: kkhosravi - (no access) - ProblemSolvingwithAlgorithmsandDataStructures.pdf, p49

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