Someone claims that the big O notation does not make sense at all, and they give the following example. An algorithm A that processes an input set of N elements takes time, in seconds, given by T(N) = 10000*N + 0.00001*N^3. They say that the large constant (10000) associated with the N will always dominate over the small constant (0.00001) associated with the N^3. You say that this algorithm A is:

Big Oh notation is used to asymptotically bound the growth of running time above and below the constant factor.

Big Oh notation is used to describe time complexity, execution time of an algorithm.

Big Oh describes the worst case to describe time complexity.

For the equation; T(N) = 10000*N + 0.00001*N^3.

To calculate first of all discard all th constants.

And therefore; worst case is the O(N^3).

were are the following commands

answer ingress;