What is new in Statistics?


The debate between two schools of thought
about statistical inference, namely frequentist and
Bayesian approach, has been taking for decades.
It is unecessary to try to argue which one is better,
simply since you can’t win!. It is not just a
matter of taste. It is so since each approach has
advantages and weaknesses. While you might get
the impression that Baysian statistics is gaining
ground in the 21st century, as testified by David
Draper (2009) (see [1]). In addition, in view of the
ban of using p-values by the Basic and Applied
Scocial Psychology (BASP) (see [2]) together with
the Statement by the American Statistical Association
recently to warn statistical practitioners about
using p-values (see [3]), it is essential to have new
statistical methods to compromise disadvantages
of those two "traditional" approaches. The Inferential
Model (IM) introduced by Ryan Martin and
Chuanhai Liu (see [4]) is a potentially candidate.