Process, Population, and Sample: the Researcher's Interest

TL;DR

This paper discusses the distinction between process and population in research, emphasizing different statistical methods for inference about processes, populations, and individual collections, including estimation and prediction techniques.

Contribution

It clarifies the conceptual difference between estimation and prediction methods and discusses their application in statistical inference about processes and populations.

Findings

Methods for interval estimation of parameters

Techniques for prediction intervals

Analytical and enumerative approaches in inference

Abstract

A case is made that researchers are interested in studying processes. Often the inferences they are interested in making are about the process and its associated population. On other occasions, a researcher may be interested in making an inference about the collection of individuals the process has generated. We will call the statistical methods employed by the researcher to make such inferences about the process/population ``estimation methods.'' The statistical methods used in making an inference about the collection of individuals generated we call ``prediction methods.'' Methods for obtaining interval estimates of a parameter and prediction intervals for a statistic are given. The analytical and enumerative methods discussed in Deming (1953) are simply estimation and prediction methods, respectively.