Please solve 1 & 2 with as much detail as possible. Thank you.

1. [30 points) a. Define computational complexity and describe its importance in evaluating/comparing algorithms b. Explain the difference between empirical runtime analysis and computational complexity c. How to determine the Big-O notation from the from T(n), the number of operations which is a function of n(the data size)? 2. [30 points Derive T(n) for the following iterative functions and determine Big-O def check(n): if n%2==0: return false i = 3 ul = math.sqrt(n) while i and array[destination - 1] > item: array( destination] = array[destination - 1] destination -= 1 array[destination] = item