Can someone tell me how I can 'normalize' my dataset? My scenario is as follows. I have two datasets, A (real-life data) and B (simulated data). Dataset A contains 4 numerical values (from an actual experiment): -> E.g. 4 leaves from a binary tree each assigned with values 12.5,13.5,20.0 and 45.0. Dataset B contains 40 numerical values (from a simulation done by the computer): -> E.g. 40 leaves from a total of 10 binary trees where each tree produces 4 leaves with randomly assigned numerical values for each leaf. For both datasets, I have computed their respective cumulative frequencies and plotted their respective charts using MS Excel e.g. [Cumulative frequencies of leaf values VS Leaf values]. This was to observe how similar/different are both of these data sets, where the smaller the vertical displacement between the two plots implies that both datasets are less different. I was instructed to normalize my data from Dataset B and re-plot the chart for a better comparison between set A and set B. How can I do this (and why is this important?)? An example based on the situation described here will help a great deal. Thanks in advance.