Startups and the Power Law Distribution of Success
https://smallbiztrends.com/2016/11/power-law-distributions-and-entrepreneurship-research.html
This article discusses how the performances of startup companies follow a power law distribution, rather than a normal distribution. It says that revenue, employment growth, and firm value indicate the performance of a startup, and that very few companies show high performance numbers, while the majority of the startups are represented by much lower numbers. It also states that many analyses of entrepreneurship throw out the higher statistics to try to make their data fit a normal distribution and prevent others from determining what firms were used in the analysis. However, these extremes are what make it a power law distribution and are the most representative of the distribution of the population.
In this course we have seen how these distributions can be modeled by f(k) = a/k^c, which indicates that a much higher number of companies fall at a lower performance mark, while very few startup companies will show a very high performance level. In this case f(k) = the number of companies with k level of performance. A few startup companies will become very successful relatively quickly and experience rapid growth, indicated by a large k, and most will move slowly and just be an average startup trying to make a name for themselves eventually.