Because you can always find a positive constant c for which following inequality hold true. A(n) <= cW(n) i.e. the avg. case time complexity always upper bounded by worst case time complexity. Which is the definition of Big O.
On Sat, Aug 25, 2012 at 7:11 PM, rahul sharma <rahul23111...@gmail.com>wrote: > *Let w(n) and A(n) denote respectively, the worst case and average case > running time of an algorithm executed on an input of size n. which of the > following is ALWAYS TRUE?* > (A) [image: A(n) = \Omega(W(n))] > (B) [image: A(n) = \Theta(W(n))] > (C) [image: A(n) = O(W(n))] > (D) [image: A(n) = o(W(n))] > > answer is c > > plz explain y??? > > -- > You received this message because you are subscribed to the Google Groups > "Algorithm Geeks" group. > To post to this group, send email to algogeeks@googlegroups.com. > To unsubscribe from this group, send email to > algogeeks+unsubscr...@googlegroups.com. > For more options, visit this group at > http://groups.google.com/group/algogeeks?hl=en. > -- You received this message because you are subscribed to the Google Groups "Algorithm Geeks" group. To post to this group, send email to algogeeks@googlegroups.com. To unsubscribe from this group, send email to algogeeks+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/algogeeks?hl=en.
