I read about Big-O notation with modular arithmetic. So, Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform. Thus the amount of time taken and the number of elementary operations performed by the algorithm differ by at most a constant factor. Some algorithms have a worst-case time of $O(n)$ or $O(n^2)$ or $O(n^3)$.What I want to know is what is the best time complexity of an algorithm? And why?
Why do compute time complexity for algorithms?
algorithms;algorithm analysis;asymptotics;runtime analysis