This project aims to identify a possible statistical relationship between the stock market and incidences of financial crime in Illinois, Texas, and Utah through big data analysis techniques using data from the FBI’s Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) database. By analyzing the occurrences of financial crime by location, year, and type in relation to the S&P 500’s percent change in close price on the first day of the calendar year, it will be possible to determine if a statistical relationship exists between the two. In addition, regression analysis was performed in order to predict financial crime incidence using stock market prices.
","abstract_html":"<p>This project aims to identify a possible statistical relationship between the stock market and incidences of financial crime in Illinois, Texas, and Utah through big data analysis techniques using data from the FBI’s Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) database. By analyzing the occurrences of financial crime by location, year, and type in relation to the S&P 500’s percent change in close price on the first day of the calendar year, it will be possible to determine if a statistical relationship exists between the two. In addition, regression analysis was performed in order to predict financial crime incidence using stock market prices.</p>","abstract_has_math":false,"creators":["Biggs, Elizabeth G"],"institution":null,"degree_name":"Mathematics","degree_level":"Thesis","degree_discipline":"Mathematics and Philosophy","degree_department":null,"school":null,"contributors":["Dr. Kristin Seamon Lilly","Dr. Ronald Linton","Dr. Brett Cotten"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-01-01T08:00:00Z","date_published":"2019-01-01T08:00:00Z","updated_at":"2026-07-24T01:45:01Z","subjects":["Stock Market","Financial Crime","Federal Bureau of Investigation's National Incident-Based Reporting System","(NIBRS)","S&P 500","Applied Mathematics","Mathematics","Numerical Analysis and Computation"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://csuepress.columbusstate.edu/theses_dissertations/328","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Kristin Seamon Lilly","Dr. Ronald Linton","Dr. Brett Cotten"]},{"key":"dc:creator","label":"Author","values":["Biggs, Elizabeth G"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-01-07T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematics and Philosophy"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Mathematics"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Stock Market","Financial Crime","Federal Bureau of Investigation's National Incident-Based Reporting System","(NIBRS)","S&P 500","Applied Mathematics","Mathematics","Numerical Analysis and Computation"]}]},{"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://csuepress.columbusstate.edu/theses_dissertations/328"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This project aims to identify a possible statistical relationship between the stock market and incidences of financial crime in Illinois, Texas, and Utah through big data analysis techniques using data from the FBI’s Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) database. By analyzing the occurrences of financial crime by location, year, and type in relation to the S&P 500’s percent change in close price on the first day of the calendar year, it will be possible to determine if a statistical relationship exists between the two. In addition, regression analysis was performed in order to predict financial crime incidence using stock market prices.
"]},{"key":"dc:title","label":"Title","values":["A Statistical Investigation of Stock Market Activity and Instances of Financial Crime"]}]}],"canonical_facts":{"dc:contributor":["Dr. Kristin Seamon Lilly","Dr. Ronald Linton","Dr. Brett Cotten"],"dc:creator":["Biggs, Elizabeth G"],"dc:date.available":["2020-01-07T08:00:00Z"],"dc:description.abstract":["This project aims to identify a possible statistical relationship between the stock market and incidences of financial crime in Illinois, Texas, and Utah through big data analysis techniques using data from the FBI’s Federal Bureau of Investigation’s National Incident-Based Reporting System (NIBRS) database. By analyzing the occurrences of financial crime by location, year, and type in relation to the S&P 500’s percent change in close price on the first day of the calendar year, it will be possible to determine if a statistical relationship exists between the two. In addition, regression analysis was performed in order to predict financial crime incidence using stock market prices.
"],"dc:identifier":["https://csuepress.columbusstate.edu/theses_dissertations/328"],"dc:language":["English"],"dc:subject":["Stock Market","Financial Crime","Federal Bureau of Investigation's National Incident-Based Reporting System","(NIBRS)","S&P 500","Applied Mathematics","Mathematics","Numerical Analysis and Computation"],"dc:title":["A Statistical Investigation of Stock Market Activity and Instances of Financial Crime"],"thesis:degree_discipline":["Mathematics and Philosophy"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Mathematics"]},"updated_at":"2026-07-24T01:45:01Z"}