The score a student earns on the PSAT is a predictor for what they earn on the SAT. Based on a student's PSAT score, we construct a Bayesian model to predict, with 95% certainty, what they will earn on their SAT. Furthermore, we explore differences in this prediction between two high schools in the same district; and ask whether the probability of improvement from the PSAT to the SAT is consistent between these two schools.
","abstract_html":"<p>The score a student earns on the PSAT is a predictor for what they earn on the SAT. Based on a student's PSAT score, we construct a Bayesian model to predict, with 95% certainty, what they will earn on their SAT. Furthermore, we explore differences in this prediction between two high schools in the same district; and ask whether the probability of improvement from the PSAT to the SAT is consistent between these two schools.</p>","abstract_has_math":false,"creators":["Brusco, Salvatore"],"institution":null,"degree_name":"MS","degree_level":"Immediate Access","degree_discipline":"Computational Mathematics","degree_department":null,"school":null,"contributors":["John Kern","Frank D'Amico","Stacey Levine","James Swindal"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-10T07:00:00Z","date_published":"2019-08-10T07:00:00Z","updated_at":"2026-07-24T02:10:50Z","subjects":[],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dsc.duq.edu/etd/1800","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["John Kern","Frank D'Amico","Stacey Levine","James Swindal"]},{"key":"dc:creator","label":"Author","values":["Brusco, Salvatore"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-08-10T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computational Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Immediate Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dsc.duq.edu/etd/1800"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The score a student earns on the PSAT is a predictor for what they earn on the SAT. Based on a student's PSAT score, we construct a Bayesian model to predict, with 95% certainty, what they will earn on their SAT. Furthermore, we explore differences in this prediction between two high schools in the same district; and ask whether the probability of improvement from the PSAT to the SAT is consistent between these two schools.
"]},{"key":"dc:title","label":"Title","values":["Score Improvement Comparison from PSAT to SAT Between two Schools"]}]}],"canonical_facts":{"dc:contributor":["John Kern","Frank D'Amico","Stacey Levine","James Swindal"],"dc:creator":["Brusco, Salvatore"],"dc:date.available":["2019-08-10T07:00:00Z"],"dc:description.abstract":["The score a student earns on the PSAT is a predictor for what they earn on the SAT. Based on a student's PSAT score, we construct a Bayesian model to predict, with 95% certainty, what they will earn on their SAT. Furthermore, we explore differences in this prediction between two high schools in the same district; and ask whether the probability of improvement from the PSAT to the SAT is consistent between these two schools.
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