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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp011831cn311
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dc.contributorMarlow, Daniel R.-
dc.contributor.advisorRomalis, Michael V.-
dc.contributor.authorSuero, Pablo-
dc.date.accessioned2015-07-24T16:05:19Z-
dc.date.available2015-07-24T16:05:19Z-
dc.date.created2015-05-04-
dc.date.issued2015-07-24-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp011831cn311-
dc.description.abstractWe explore various methods for the recognition and analysis of systematic errors in experiments whose errors come from different distributions, or are not gaussian distributed. First, we explore a method for detecting whether linear-looking data actually has a squared term dependency in it. Then, we apply the bootstrap method to calculate confidence intervals in the presence of 1/f noise.en_US
dc.format.extent36 pagesen_US
dc.language.isoen_USen_US
dc.titleAnalysis of Systematic Errors in Experiments with Variable Errorsen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2015en_US
pu.departmentPhysicsen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Physics, 1936-2020

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