Explain why each is wrong or right

Identify what is true: An algorithm with amortized complexity of O(Nlog(N)) can have individual operations that grows as N"N The input is essential when determining the worst and best case performance of an algorithm Tilde and Big-Oh analyses serve to determine how the worst case of an algorithm grows when the size of the problem grows Tilde-notation is the same as Big-Oh notation Amortized complexity means that the cost of executing costly operations can be amortized over less costly operations An algorithm that is Big-Omega(N) is always faster than a O(NlogN) algorithm for large When determining tilde approximations and/or the Big-Oh classification of a problem one should, in most cases, determine the "inner loop" of the algorithm An O(log(N)) algorithm is always faster than an O(N) algorithm for all N