ASAP i will give you a like when you complete that

Question 17 1 pts Big O is a useful estimate of an algorithm's "worst case" complexity, but there are other factors to consider when selecting an algorithm for a given problem. Which of the following factors may be worth considering? i. How much memory the algorithm takes ii. The constant coefficients in the complexity formula iii. The typical or average complexity of the algorithm iv. The "best case" (omega) complexity of the algorithm v. What input sizes you expect to use vi. How often you will need to run the algorithm O vonly O i only Oiv only ll only Oil only vi only Oliv, v,vi Question 18 1 pts The Master Theorem helps us find the Big-O of "divide and conquer" recurrence relations of the form T(n) = aT(n/b) + f(n) To use it, compare the value of logba to the exponent of f(n). What are the three cases of the Master Theorem? (logba > the exponent of f(n) O(nl) (logia the exponent of f(n)) - Of(n)) (logoa the exponent of f(n)) OffinHogan) logoa the exponent of ) - Offin-oggn) O loga -- the exponent off) - Olno) (loga the exponent of f(n)) - Ofrogan) Question 8 1 pts What is the correct pronunciation of O(na) in spoken English? Onto O Big Oh of n squared We speak not its name! Big Theta of n squared Big Omega of n squared Question 9 1 pts What is the correct pronunciation of O(n) in spoken English? O Fear of a name only increases fear of the thing itself, Big Oh of n squared Big Omega of n squared Big Theta of n squared Onto Question 10 1 pts What is the correct pronunciation of O(n) in spoken English? Big Theta of n squared Big Omega of n squared Voldemort. There, I said it. Onto Big Oh of n squared