Practical Problems of Statistical Learning

Statistical models have seen a significant rise in popularity in recent years. Despite their undeniable success in various industry use cases such as sabermetrics, investment portfolio management, and artificial intelligence, there has been immense debate about the value of results produced by statistical methods. This paper focuses on presenting the common issues practitioners have when implementing statistical learning models, and why these issues make it difficult to interpret results produced by such methods.