Q4. What is the T(n) and big O performance of the following function? This function gets a value as an input and prints all prime numbers between 1 and the input number. Math.sqrt takes the square root of a number import math def print all primes (n) : for num in range (1, n + 1) : isPrime = True for i in range (2, int (1+math . sqrt (num) ) ) : if num $ i ==0 : isPrime = False break if isPrime : print (num) Which one is faster? sorting a list of size n or to printing all prime numbers up to n? Answer based on both bubble sort and merge sort.Q5. Assume that that after analysing a recursive function to find it's T(n) you find that T(n) = 5+ 2 * T(n/4) What is the big O performance of this function? Is it faster or slower than binary search? Is it faster or slower than merge sort? Hint: a ^ ( log x in base a^k) = x^(1/k)

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What is the T(n) and big O performance of the following function? This function gets a value as an input and prints all prime numbers between 1 and the input number. Math.sqrt takes the square root of a number import math def print_all_primes (n): for num in range (1, n + 1): is Prime True for i in range (2, int (1+math.sqrt(num))): if numi ==0 : is Prime = False break if isPrime: print (num) Which one is faster? sorting a list of size n or to printing all prime numbers up to n? Answer based on both bubble sort and merge sort. What is the T(n) and big O performance of the following function? This function gets a value as an input and prints all prime numbers between 1 and the input number. Math.sqrt takes the square root of a number import math def print_all_primes (n): for num in range (1, n + 1): is Prime True for i in range (2, int (1+math.sqrt(num))): if numi ==0 : is Prime = False break if isPrime: print (num) Which one is faster? sorting a list of size n or to printing all prime numbers up to n? Answer based on both bubble sort and merge sort.