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The purpose of this chapter is to discuss the conceptual, methodological, and statistical challenges in selecting appropriate peer institutions for comparative purposes. The authors' approach embraces a Western scientific tradition that physical things and phenomena can be "reduced into a set of key variables--identifiable parts--that make key contributions, and that the behavior of the whole--in this case institutions of higher education--can be understood by knowing the parts and how they contribute (behave)." Furthermore, a value is placed on "efficiency" and "effective (successful) outcomes." These assumptions have spawned a number of models that stress in varying degrees the larger environmental, "structural and/or contextual variables and 'inputs-processes-outputs.'" Input-processes-outputs models are central to comparative analyses in general and benchmarking in particular. A representation of a general benchmarking model is provided. This point of view frames the conceptual and methodological issues and the technique of principal components analysis the authors discuss in this chapter. (Contains 4 tables, 6 figures, and 4 notes.)

Mills' capture-recapture sampling method allows the estimation of the number of errors in a program by randomly inserting known errors and then testing the program for both inserted and indigenous errors. This correspondence shows how correct confidence limits and maximum likelihood estimates can be obtained from the test results. Both fixed sample size testing and sequential testing are considered. [ABSTRACT FROM AUTHOR]

Addresses issues discussed as commentaries on a study that used statistical methods in the evaluation of fossil fuels. Economics and statistical models criticized in the study; Response on the criticisms against the review of statistics used in the study; Clarification on the reported confidence intervals in the reserve estimates. [ABSTRACT FROM AUTHOR]