Why is the average-case running time of quicksort $O(n log_2 n)$?
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What is a mathematically rigorous explanation of why quicksort's average-case running time is $O(n log_2 n)$?
algorithms
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$begingroup$
What is a mathematically rigorous explanation of why quicksort's average-case running time is $O(n log_2 n)$?
algorithms
$endgroup$
add a comment |
$begingroup$
What is a mathematically rigorous explanation of why quicksort's average-case running time is $O(n log_2 n)$?
algorithms
$endgroup$
What is a mathematically rigorous explanation of why quicksort's average-case running time is $O(n log_2 n)$?
algorithms
algorithms
asked Dec 6 '18 at 7:22
Austin ConlonAustin Conlon
2621412
2621412
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1 Answer
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To do average case analysis, we need to consider all possible permutation of the input array and calculate the time taken by every permutation which is not easy. We can get an idea of average case by considering the case when partition cuts $O(frac{n}{9})$ elements in one set and $O(frac{9n}{10})$ elements in other set. Following this we get
begin{equation}
T(n) = T(frac{n}{9}) + T(frac{9n}{10}) + O(n)
end{equation}
which is shown to be $O(n log n)$. If you average over all such permutations, you will also get $O(n log n)$.
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
To do average case analysis, we need to consider all possible permutation of the input array and calculate the time taken by every permutation which is not easy. We can get an idea of average case by considering the case when partition cuts $O(frac{n}{9})$ elements in one set and $O(frac{9n}{10})$ elements in other set. Following this we get
begin{equation}
T(n) = T(frac{n}{9}) + T(frac{9n}{10}) + O(n)
end{equation}
which is shown to be $O(n log n)$. If you average over all such permutations, you will also get $O(n log n)$.
$endgroup$
add a comment |
$begingroup$
To do average case analysis, we need to consider all possible permutation of the input array and calculate the time taken by every permutation which is not easy. We can get an idea of average case by considering the case when partition cuts $O(frac{n}{9})$ elements in one set and $O(frac{9n}{10})$ elements in other set. Following this we get
begin{equation}
T(n) = T(frac{n}{9}) + T(frac{9n}{10}) + O(n)
end{equation}
which is shown to be $O(n log n)$. If you average over all such permutations, you will also get $O(n log n)$.
$endgroup$
add a comment |
$begingroup$
To do average case analysis, we need to consider all possible permutation of the input array and calculate the time taken by every permutation which is not easy. We can get an idea of average case by considering the case when partition cuts $O(frac{n}{9})$ elements in one set and $O(frac{9n}{10})$ elements in other set. Following this we get
begin{equation}
T(n) = T(frac{n}{9}) + T(frac{9n}{10}) + O(n)
end{equation}
which is shown to be $O(n log n)$. If you average over all such permutations, you will also get $O(n log n)$.
$endgroup$
To do average case analysis, we need to consider all possible permutation of the input array and calculate the time taken by every permutation which is not easy. We can get an idea of average case by considering the case when partition cuts $O(frac{n}{9})$ elements in one set and $O(frac{9n}{10})$ elements in other set. Following this we get
begin{equation}
T(n) = T(frac{n}{9}) + T(frac{9n}{10}) + O(n)
end{equation}
which is shown to be $O(n log n)$. If you average over all such permutations, you will also get $O(n log n)$.
answered Dec 6 '18 at 7:37
Ahmad BazziAhmad Bazzi
8,3622824
8,3622824
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