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4. Since Big-O notation is a mathematical tool for functions like f(N) or g(N), how is it applicable to algorithm analysis? 5. Which grows faster,
4. Since Big-O notation is a mathematical tool for functions like f(N) or g(N), how is it applicable to algorithm analysis?
5. Which grows faster, 2^n or n! ? Why?
6. Give the Big-O notation for the following expressions:
a. 4n^5 + 3n^2 - 2
b. 5^n - n^2 + 19
c. (3/5)*n d. 3n * log(n) + 11
e. [n(n+1)/2 + n] / 2
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