MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • Operations Research Center
  • Operations Research Center Working Papers
  • View Item
  • DSpace@MIT Home
  • Operations Research Center
  • Operations Research Center Working Papers
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Preliminary Survey of Classical Statistical Techniques for Incorporation into Adaptive Evaluation Methodology

Author(s)
Minkoff, Alan S.
Thumbnail
DownloadOR-110-81.pdf (2.056Mb)
Metadata
Show full item record
Abstract
Evaluation of public programming currently tends toward plans that are set in advance of any sampling and adhered to throughout. Because increments in the knowledge profile during the course of an evaluation might beckon adjustment of the working procedure, fixed evaluation methodology may be cost-inefficient. It is desired to develop a methodology that is adaptive to changes in the knowledge profile. This might be most easily accomplished by borrowing ideas from some of the disciplines in which relevant problems occur. The most promising fields for this task include classical and Bayesian statistics, reliability theory, and dynamic programming. This paper reviews the techniques in classical statistics that seem most apt for handling the problem of adaptive changes in an evaluation to updated knowledge profiles, and considers the paths along which future research ought to be conducted.
Date issued
1981-02
URI
http://hdl.handle.net/1721.1/5172
Publisher
Massachusetts Institute of Technology, Operations Research Center
Series/Report no.
Operations Research Center Working Paper;OR 110-81

Collections
  • Operations Research Center Working Papers

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.