Algorithm performance coverage in textbooks emphasizes patterns of growth in execution times, relative to the size of the problem. Variability in execution times for a given problem size is usually ignored. In this research study, our primary focus is on the empirical distribution of execution times for a given algorithm and problem size. We examine CPU times for Java implementations of five sorting algorithms for arrays: selection sort, insertion sort, shell sort, merge sort, and quicksort. We measure variation in running times for these algorithms and describe how the sort-time distributions change as the problem size increases. Using our research methodology, we compare the relative stability of performance for the different sorting algorithms.