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Parametric Estimating

&

the Stepwise Statistical Technique

J. L. Robbins

“The important question about methods is not ‘how’ but ‘why’”

Tukey.

Introduction

Statistical analysis of data sets is seemingly a relatively straight-forward process wherein the analyst gathers data and applies statistical techniques for decision-making. It is a process that is approached and accomplished by analysts in the DoD cost estimating environment on a daily basis. It is a process that generates much intellectual intrigue, dialogue and, not infrequently, controversy. For example, the theorist functioning in a purely academic realm is in a position to significantly influence his or her research design and thereby insure both control and volume of data, whereas the analyst functioning in a DoD cost estimating environment generally is restricted to existing data bases and wrestling with time constraint issues, age of technology and viability of statistical models. In essence, the approach to statistical analysis of data sets is dependent upon the analyst’s environment. Hence, there is an endless source of information on statistical techniques and how to use them and it is the ‘how’ that often drives the process; i.e., the analyst tends to formulate “...problems in a way which requires for their solution just those techniques in which he himself is especially skilled” (Pedhazur, 1982, p. 4).

Stepwise regression is one technique; however, that does face intense controversy regardless of the analyst’s environment. This controversy abounds in nearly all areas regardless of whether the analyst has a social science prospective or a DoD prospective. Therefore, the purpose of this article is to briefly highlight some of the rationale that contributes to this controversy, to illustrate the stepwise regression analysis technique with a hypothetical data set and to summarize key characteristics about use and limitations of the technique. This article will in no...