To normalize a set of negative values for plotting a normal distribution graph, traditional methods like (X-mu)/sigma may not be effective due to the inherent nature of the data. Transforming the data using a function y = f(x) is necessary to achieve a normal distribution, but the choice of function depends on the original distribution and the context of the data. Understanding the graphical attributes and statistical characteristics of the data is crucial for selecting the appropriate transformation. Simply applying an exponential function may not suffice without considering these factors. Normalizing negative data is a complex process that requires careful analysis and consideration.