The increasing coverage in the recent literature of comparison studies between the European and American entrepreneurial ecosystems indicates an ever-increasing need for tools that facilitate the understanding of entrepreneurial phenomena to facilitate the necessary economic and political changes in support of innovation. Other interesting recent literature supports a shift in probability distributions assumed in entrepreneurship research from the Gaussian distributions to heavy-tailed ones. This thesis tries to develop a method that combines the two research trends above. Firstly, it tries to inquire about the distributions of three of the most common variables of interest in entrepreneurship used to describe the financial story of a startup: total funding, exit value and multiple on invested capital (MOIC).