Need help please on this discrete math problem Moe, Larry, and Curly have just purchased three new computers and use three different algorithms to sort lists:| | Comparisons / sec | Search Algorithm | \( T(n) \) ||---------------|-------------------|------------------------|------------|| Moe | 50 | Linear Search | \( n \) || Larry | 5 | Optimal Chunk Search | \( 2\sqrt{n} \) || Curly | 1 | Binary Search | \( \log_2 n \) |where \( T(n) \) is the number of comparisons it takes, in the worst case, to sort a list of size \( n \).How large must \( n \) be to ensure that, for every list, ... iii. Curly's computer sorts faster than Larry's?(Note: There are no graphs or diagrams in the image.)

Actually, in sorting the elements are in order,(ascending or descending).Solution ;-Moe, Larry, and Curly have just purchased three new computers. Moe’s computer is 10 times faster than Larry’s and 50 times faster than Curly’s. For parts of this problem, you will have to solve an equation that involve (or ) and . Such equations typically cannot be solved analytically, i.e., by applying the rules of algebra to obtain a formula for . Such equations are often solved numerically by using binary search! Consider the equation- First, find two initial values of , one of which causes the left-hand side of the equation to exceed the right, and the other of which causes the right-hand side of the equation to exceed the left. The solution to the equation lies somewhere between these two values. For example, when = 2, the left-hand side of the equation is 10 while the right-hand side is 2. Conversely, when = 128, the left-hand side is 70 while the right-hand side is 128. The solution to this equation lies somewhere between = 2 and = 128. One could then apply binary search in this range to find the solution in question. (Think about which half of the interval one should search and why.)

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Moe, Larry and Curly have just purchased three new computers and use three different algorithms to sort lists: T(n) Search Algorithm Linear Search Comparisons / sec Moe 50 (l EST Larry Curly Optimal Chunk Search 2n log2 n 1 Binary Search where T(n) is the number of comparisons it takes, in the worst case, to sort a list of size n. How large must n be to ensure that, for every list, ...

Moe, Larry and Curly have just purchased three new computers and use three different algorithms to sort lists: T(n) Search Algorithm Linear Search Comparisons / sec Moe 50 (l EST Larry Curly Optimal Chunk Search 2n log2 n 1 Binary Search where T(n) is the number of comparisons it takes, in the worst case, to sort a list of size n. How large must n be to ensure that, for every list, ...

C++ Programming: From Problem Analysis to Program Design

8th Edition

ISBN:9781337102087

Author:D. S. Malik

Publisher:D. S. Malik

Chapter16: Searching, Sorting And Vector Type

Section: Chapter Questions

Problem 6PE

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Question

Need help please on this discrete math problem

Moe, Larry, and Curly have just purchased three new computers and use three different algorithms to sort lists:

| | Comparisons / sec | Search Algorithm | \( T(n) \) |
|---------------|-------------------|------------------------|------------|
| Moe | 50 | Linear Search | \( n \) |
| Larry | 5 | Optimal Chunk Search | \( 2\sqrt{n} \) |
| Curly | 1 | Binary Search | \( \log_2 n \) |

where \( T(n) \) is the number of comparisons it takes, in the worst case, to sort a list of size \( n \).

How large must \( n \) be to ensure that, for every list, ...

iii. Curly's computer sorts faster than Larry's?

(Note: There are no graphs or diagrams in the image.)

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