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Best selling The Art of Statistics notes
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CSE 551: Quiz 4 Solutions
- Other • 7 pages • 2021 Popular
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- $13.99
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1 Problem 1 
Solve the following recurrence relation using any method. Provide your 
answer in big-O notation: T(n) = 2T( 
n 
2 
) + log(n) for n > 1, 0 otherwise 
• T(n) = O(n) 
• T(n) = O(nlogn) 
• T(n) = O(n 
2 
) 
• T(n) = O(logn) 
1.1 Rationale 
This recurrence relation can be tricky to solve using iterative substitution 
or tree-based methods. It’s best to use the Master theorem here. Recall the 
form: 
T(n) = aT(n/b) + f(n) 
Since f(n) = log(n) = n 
 where < log2(2) = 1...
Newest The Art of Statistics summaries
-
CSE 551: Quiz 4 Solutions
- Other • 7 pages • 2021 New
-
- $13.99
- + learn more
1 Problem 1 
Solve the following recurrence relation using any method. Provide your 
answer in big-O notation: T(n) = 2T( 
n 
2 
) + log(n) for n > 1, 0 otherwise 
• T(n) = O(n) 
• T(n) = O(nlogn) 
• T(n) = O(n 
2 
) 
• T(n) = O(logn) 
1.1 Rationale 
This recurrence relation can be tricky to solve using iterative substitution 
or tree-based methods. It’s best to use the Master theorem here. Recall the 
form: 
T(n) = aT(n/b) + f(n) 
Since f(n) = log(n) = n 
 where < log2(2) = 1...
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