Statistical methods (SM) have been dominant in generating insights from any type of data for generations. However, with the recent advances in technology, machine learning(ML) has become one of the widely spoken methods to generate insights with more ease of use.
While the followers of statistical methods have a differing view point about ML, and the followers of ML have a differing viewpoint about SM, we understand the merits of each of these two methods and advances arguments for when to use what method based on the purpose, context, frequency of use, cost, expertise and time.
To be specific, the main purpose of SM is for inference and that of ML is prediction. We combine the learnings from using a statistical method and apply it to machine learning, the ultimate benefit can be greater than the sum of each method’s benefits.