computational complexity multi-tasking system another factor is likely the caching of memory locations cache is way of speeding up access to memory in some situations and it is likely that the really low access times benefited from the existence of cache for the ram of the computer the experimental data backs up the claim that the size of list does not affect the average access time in the list the blue line in the plot is the result of doing list retrieval and store operations on one list of , elements the reason the blue line is higher than the red line is likely the result of doing both retrieval from and store operation into the element of the list in additionthe further apart the values in memorythe less likely cache will help reduce the access time whatever the reason for the blue line being higher the important thing to notice is that accessing the element at index takes no more time than accessing any other element of the sequence all locations within the list are treated equally this backs up the claim that the average access time at any location within list is the sameregardless of its location within the list big-oh notation whichever line we look at in the experimental datathe access time never exceeds us for any of the memory accesseseven with the other things the computer might be doing we are safe concluding that accessing memory takes less than us in fact us is much more time than is needed to access or store value in memory location our experimental data backs up the two claims we made earlier howevertechnicallyit does not prove our claim that accessing memory takes constant amount of time the architecture of the ram in computer could be examined to prove that accessing any memory location takes constant amount of time accessing memory is just like calling out name in group of people and having that person respond with the value they were assigned it doesn' matter which person' name is called out the response time will be the sameor nearly the same the actual time to access the ram of computer may vary little bit if cache is availablebut at least we can say that there is an upper bound to how much time accessing memory location will take this idea of an upper bound can be stated more formally the formal statement of an upper bound is called big-oh notation the big-oh refers to the greek letter omicron which is typically used when talking about upper bounds as computer programmersour number one concern is how our programs will perform when we have large amounts of data in terms of the memory of computerwe wanted to know how our program would perform if we have very large list of elements we found that all elements of list are accessed in the same amount of time independent of how big this list is let' represent the size of the list by variable called let the average access time for accessing an element of list of size be given by (nnow we can state the following ( ( ) this copy belongs to 'acha