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'''Square root biased sampling''' is a [[sampling (statistics)|sampling]] method proposed by [[William H. Press]], a [[computer sciences|computer scientist]] and [[computational biology|computational biologist]], for use in [[Airport security|airport screenings]]. It is the mathematically optimal compromise between [[Simple_random_sample|simple random sampling]] and [[Offender profiling|strong profiling]] that most quickly finds a rare malfeasor, given fixed screening resources.<ref name="the paper">{{Cite journal
  | last = Press
  | first = William H.
  | authorlink =
  | coauthors =
  | title = Strong profiling is not mathematically optimal for discovering rare malfeasors
  | journal = Proceedings of the National Academy of Sciences
  | volume = 106
  | issue = 6
  | pages = 1716–1719
  | publisher =
  | location =
  | date = February 10, 2009
  | url = http://www.pnas.org/content/106/6/1716.full
  | doi = 10.1073/pnas.0813202106
  | id =
  | accessdate = 2009-11-28}}</ref><ref name="homeland"></ref>


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Using this method, if a group is <math alt="n">n</math> times as likely as the average to be a security risk, then persons from that group will be <math alt="square root of n">\sqrt{n}</math> times as likely to undergo [[Airport_security#Process_and_equipment|additional screening]].<ref name="the paper"></ref> For example, if someone from a profiled group is nine times more likely than the average person to be a security risk, then when using [[square root]] biased sampling, people from the profiled group would be screened three times more often than the average person.
 
==History==
Press developed square root biased sampling as a way to sample long sequences of [[DNA]].<ref name="texas"/> It had also been developed independently by Ruben Abagyan, a professor at [[Scripps Research Institute|TSRI]] in La Jolla, California, for use in a different biological context.<ref>Abagyan RA, Totrov M (1999) "Ab initio folding of peptides by the optimal-bias Monte Carlo minimization procedure", Journal of Computational Physics, vol. 151, pp. 402-421.</ref><ref>Zhou Y, Abagyan R (2002) "Efficient stochastic global optimization for protein structure prediction", Rigidity  Theory and Applications, eds. Thorpe MF, Duxbury PM (New York, Springer).</ref> An even earlier discovery was by Martin L. Shooman, who used square root biased sampling in a test apportionment model for software reliability.<ref>M.L. Shooman, "A micro software reliability model for prediction and test apportionment," Proceedings 1991 International Symposium on Software Reliability Engineering (IEEE, 1991), pp. 52-59.</ref>
 
Press' later proposal to use square root biased sampling for airport security was published in 2009.<ref name="the paper"/> There, he argued that this method would be a more efficient use of the limited resources possessed for screening, as compared to the current practice, which can lead to screening the same persons frequently and repeatedly.<ref name="homeland">{{Cite news
  | last =
  | first =
  | author-link =
  | last2 =
  | first2 =
  | author2-link =
  | title = Square root bias and airport security screening
  | newspaper = Homeland Security Newswire
  | pages =
  | year = 2009
  | date = 2009-02-03
  | url = http://homelandsecuritynewswire.com/square-root-bias-and-airport-security-screening
  | accessdate = 2009-11-28
  | postscript = <!-- Bot inserted parameter. Either remove it; or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}
}}</ref><ref name="texas">{{Cite news
  | last =
  | first =
  | coauthors =
  | title = Researcher Proposes Statistical Method to Enhance Secondary Security Screenings
  | newspaper =
  | location =
  | pages =
  | language =
  | publisher = University of Texas at Austin News
  | date = 2009-02-03
  | url = http://www.utexas.edu/news/2009/02/03/statistical_security/
  | accessdate = 2009-11-28}}
</ref> However, use of this method presupposes that those doing the screening have accurate [[statistical]] information on who is more likely to be a security risk, which is not necessarily the case.<ref>William Press, "To catch a terrorist: can ethnic profiling work?", Significance, December 2010, p. 164.</ref>
 
==See also==
* [[Numerical Recipes]], a series of books on [[algorithm]]s and [[numerical analysis]] coauthored by William Press.
 
==References==
{{reflist}}
 
[[Category:Sampling techniques]]
[[Category:Risk]]
 
 
Derivation and application: http://www.soa.org/files/pd/erm/2010-chicago-erm-sem3.pdf

Latest revision as of 22:25, 20 August 2013

Square root biased sampling is a sampling method proposed by William H. Press, a computer scientist and computational biologist, for use in airport screenings. It is the mathematically optimal compromise between simple random sampling and strong profiling that most quickly finds a rare malfeasor, given fixed screening resources.[1][2]

Using this method, if a group is times as likely as the average to be a security risk, then persons from that group will be times as likely to undergo additional screening.[1] For example, if someone from a profiled group is nine times more likely than the average person to be a security risk, then when using square root biased sampling, people from the profiled group would be screened three times more often than the average person.

History

Press developed square root biased sampling as a way to sample long sequences of DNA.[3] It had also been developed independently by Ruben Abagyan, a professor at TSRI in La Jolla, California, for use in a different biological context.[4][5] An even earlier discovery was by Martin L. Shooman, who used square root biased sampling in a test apportionment model for software reliability.[6]

Press' later proposal to use square root biased sampling for airport security was published in 2009.[1] There, he argued that this method would be a more efficient use of the limited resources possessed for screening, as compared to the current practice, which can lead to screening the same persons frequently and repeatedly.[2][3] However, use of this method presupposes that those doing the screening have accurate statistical information on who is more likely to be a security risk, which is not necessarily the case.[7]

See also

References

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.


Derivation and application: http://www.soa.org/files/pd/erm/2010-chicago-erm-sem3.pdf

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  2. ↑ 2.0 2.1 Template:Cite news
  3. ↑ 3.0 3.1 Template:Cite news
  4. ↑ Abagyan RA, Totrov M (1999) "Ab initio folding of peptides by the optimal-bias Monte Carlo minimization procedure", Journal of Computational Physics, vol. 151, pp. 402-421.
  5. ↑ Zhou Y, Abagyan R (2002) "Efficient stochastic global optimization for protein structure prediction", Rigidity Theory and Applications, eds. Thorpe MF, Duxbury PM (New York, Springer).
  6. ↑ M.L. Shooman, "A micro software reliability model for prediction and test apportionment," Proceedings 1991 International Symposium on Software Reliability Engineering (IEEE, 1991), pp. 52-59.
  7. ↑ William Press, "To catch a terrorist: can ethnic profiling work?", Significance, December 2010, p. 164.
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