I’ve been thinking a lot about replacing statistics with machine learning and how one could go about that. I previously tried arguing that the “roots” of a lot of classical statistical approaches are flawed, i.e. they make too many assumptions about the world and thus lead to faulty conclusions and overly complex models with no real insight.
I kind of abandoned that avenue once I realized people back in the late 60s and early 70s were making that point and proposing what are now considered machine learning techniques as a replacement.
I’ve been thinking a lot about replacing statistics with machine learning and how one could go about that. I previously tried arguing that the “roots” of a lot of classical statistical approaches are flawed, i.e. they make too many assumptions about the world and thus lead to faulty conclusions and overly complex models with no real insight.
I kind of abandoned that avenue once I realized people back in the late 60s and early 70s were making that point and proposing what are now considered machine learning techniques as a replacement.
So instead I’ve decided to just focus any further anger at bad research and people using nonsensical constructs like p-value on trying to popularize better approaches based on predictive modeling.