Analyzing Singleton Sort Through Computer Experiments for Normal Inputs

The present work aims to study the behavior of singleton sort algorithm for normal distribution inputs with a focus on parameterized complexity. Statistical bound estimates are obtained by running computer experiments working directly on time. It is found, using factorial experiments, that the parameters of normal distribution ( mean and standard deviation) along with the input size are all significant statistically both individually as well as interactively.