Success Stories of "Statistics"? When it comes to Machine Learning, the successful application seem to be very well known. For example, Neural Networks have been successfully used to create Self Driving Cars and Game Playing Algorithms (e.g. Go, Chess).
When we think of classical statistical models such as regression model, it seems more difficult to think of equally well known and successful applications of such models.
I understand that this might be in part because Machine Learning might get more news/media attention and the problems in which Machine Learning tends to be applied in are in some ways easier to quantify success - e.g. does this neural network beat the world champion?. I also understand that Machine Learning itself is heavily rooted in statistics, e.g. PAC learnability.
But in terms of the classical statistical models such as regression, have their been any successful applications of these models on a similar scale to the successful applications of machine learning?
Thanks!


When we think of classical statistical models such as regression model, it seems more difficult to think of equally well known and successful applications of such models.


But in terms of the classical statistical models such as regression, have their been any successful applications of these models on a similar scale to the successful applications of machine learning?

Although there are many unsuccessful or wrong applications in science, I would say that science is for a large part a demonstration of successful applications.
To answer the question why classical models aren't often in the news, let's divide statistics in the inference and algorithmic viewpoints (Efron & Hastie, 2021) or, similarly, the prediction and explanation viewpoints (Yarkoni & Westfall, 2017).
Then, your machine learning examples all belong in the prediction category.
I think these obtain so much attention because they offer the basis for automated systems.
Even more so, they offer automated models which companies can use to earn money with, so they are incentivized to spend money on selling the models.
Conversely, successful applications of inference often do not mention the model; only the outcome.
