Simulating Average Case Time Complexity Of Sample Random Sampling Without Replacement
by
Anchala Kumari
Department of Statistics, Patna University, India
Coauthors: S. Chakraborty (Bhagalpur University, India)

In the era of speed, faster computing has ever been of great concern. The objective lies in finding optimal algorithm for a given problem . Developing an algorithm with least asymptotic execution time is one aspect ,while the minimum number of operations required to compute a given function being the another offshoot .Commonly , the order of complexity of a given problem is expressed simply by counting the minimum number of operations required and this in turn is expressed in terms of the input parameters .Expressing the order of complexity merely by counting the number of operations , will not serve the purpose of finding optimal algorithm rather we must be motivated to seek some real and robust measure for the same, as well as inner mechanism contributing to it.

In this paper an attempt has been made to simulate the average case time complexity of simple random sampling using statistical approach. The estimate of parameters of the model have also been obtained but the focus is on the pattern recognition than on the estimation since the estimates are system dependent.

Date received: July 8, 2003