(THE ANSWER BELOW IS WRONG!! Please give me an answer other than the one below) Please find below the answers along with

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(THE ANSWER BELOW IS WRONG!! Please give me an answer
other than the one below)
Please find below the answers along with explanations for the
first four questions as per the answering guidelines...
1.a
The master method is a formula for solving recurrence relations
of the form:
An asymptotically positive function means that for a
sufficiently large value of n, we have f(n) > 0.
The master theorem is used in calculating the time complexity of
recurrence relations (divide and conquer algorithms) in a simple
and quick way.
Master Theorem
If a ≥ 1 and b > 1 are constants and f(n) is an
asymptotically positive function, then the time complexity of a
recursive relation is given by
Each of the above conditions can be interpreted as:
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The actual question. Please show me the answer step by
step.

The Answer Below Is Wrong Please Give Me An Answer Other Than The One Below Please Find Below The Answers Along With 1 (123.41 KiB) Viewed 34 times

PYTHON PROGRAMMING Problem 1 A) Use the Master's Theorem to design a function (it can do anything you want it to) that has an O(n1.6...) complexity. The first two digits should be 1.6 Note: We usually classify the complexity of our algorithms using common Big 0 sets such as O(n), O(n), O(n log n). However, for o this exercise, we will use the Big O set the master's theorem gives. Hint: You may want to use binary() (used as a recursion) as a starting point. Explain your thought process. n T(n) =a x T (7) + f(n) 1. if O(f(n)) < nlog, a, then O(T(n)) = nlog, a 2. if O(f(n)) = nlog, a, then O(T(n)) = nlogga lg n 3. if O(f(n)) > nlog, a, then O(T(n)) = (f(n)) = = B) Without changing the constant “a” and the “f(n)" you used in the master's theorem equation, use the function you made for the previous subquestion to design a O(n2.6...) algorithm. Hint. Use the function as a blackbox function within another function.