ABSTRACT
Currently most statistical analyses generally involve inferences or decisions about parameters or indexes of statistical distributions. It is the view of this author that analyzers of data would better serve their clients if inferences and decisions were couched in an observabilistic or predictivistic framework. The focus on parametric statistical analysis arose from the measurement error model. Here some real physical entity was to be measured but the measuring instrument was subject to error. Hence the observed value was modeled as X = θ + e https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9780203742310/579ac1f2-f40a-4dc7-b13d-cf4179828552/content/eq1.tif"/>
