{"id":{"repo_id":"regina","oai_identifier":"oai:uregina.scholaris.ca:10294/17141"},"canonical_url":"https://search.dev.ndltd.org/etd/regina/oai:uregina.scholaris.ca:10294/17141","repository":{"repo_id":"regina","name":"University of Regina","base_url":"https://uregina.scholaris.ca/server/oai/request"},"display":{"title":"Confidence estimation of the ratio of variances of two log-normal populations","abstract":"This study investigates asymptotic and bootstrap confidence intervals (CIs) for the ratio of variances of two independent log-normal distributions. Extensive simula-tions were conducted to evaluate the performance of these CIs under varying sample sizes (10 to 350) and variance ratios, with one variance fixed at 0.1 and the other varying from 0.1 to 2.0. The impacts of equal and unequal were studied. The results reveal that the asymptotic CI performs well for small variance differences, especially with moderate to large sample sizes, while bootstrap CIs outperform it for larger variance differences. Notably, the t-bootstrap CI excels when both the variance dif-ference and sample sizes are large, whereas the percentile and standard bootstrap CIs are preferable for small variance differences. The study also demonstrates the practical application of these methods using PM2.5 mass concentration data from two industrial sites in Thailand, confirming their effectiveness in real-world scenarios. Keywords: Log-normal distribution, Ratio of variances, Asymptotic confidence inter-val, Bootstrap confidence interval.","abstract_html":"This study investigates asymptotic and bootstrap confidence intervals (CIs) for the ratio of variances of two independent log-normal distributions. Extensive simula-tions were conducted to evaluate the performance of these CIs under varying sample sizes (10 to 350) and variance ratios, with one variance fixed at 0.1 and the other varying from 0.1 to 2.0. The impacts of equal and unequal were studied. The results reveal that the asymptotic CI performs well for small variance differences, especially with moderate to large sample sizes, while bootstrap CIs outperform it for larger variance differences. Notably, the t-bootstrap CI excels when both the variance dif-ference and sample sizes are large, whereas the percentile and standard bootstrap CIs are preferable for small variance differences. The study also demonstrates the practical application of these methods using PM2.5 mass concentration data from two industrial sites in Thailand, confirming their effectiveness in real-world scenarios. Keywords: Log-normal distribution, Ratio of variances, Asymptotic confidence inter-val, Bootstrap confidence interval.","abstract_has_math":false,"creators":["Tantikhajorngosol, Puttipong"],"institution":"Faculty of Graduate Studies and Research, University of Regina","degree_name":"Master of Science (MSc)","degree_level":null,"degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":[],"advisors":["Volodin, Andrei"],"committee_chairs":[],"committee_members":["Sardarli, Arzu"],"year":2025,"date_issued":"2025-07","date_published":"2025-07","updated_at":"2026-07-24T04:03:32Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/161"],"render_values":[{"text":"https://doi.org/10.82465/161","href":"https://doi.org/10.82465/161","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/10294/17141","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Volodin, Andrei"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Sardarli, Arzu"]},{"key":"dc:creator","label":"Author","values":["Tantikhajorngosol, Puttipong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-06-08T20:16:09Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-07"]},{"key":"dc:publisher","label":"Institution","values":["Faculty of Graduate Studies and Research, University of Regina"]},{"key":"dc:type","label":"Dc Type","values":["master thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MSc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Regina"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.82465/161"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10294/17141"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Statistics, University of Regina. viii, 99 p."]},{"key":"dc:description.abstract","label":"Abstract","values":["This study investigates asymptotic and bootstrap confidence intervals (CIs) for the ratio of variances of two independent log-normal distributions. Extensive simula-tions were conducted to evaluate the performance of these CIs under varying sample sizes (10 to 350) and variance ratios, with one variance fixed at 0.1 and the other varying from 0.1 to 2.0. The impacts of equal and unequal were studied. The results reveal that the asymptotic CI performs well for small variance differences, especially with moderate to large sample sizes, while bootstrap CIs outperform it for larger variance differences. Notably, the t-bootstrap CI excels when both the variance dif-ference and sample sizes are large, whereas the percentile and standard bootstrap CIs are preferable for small variance differences. The study also demonstrates the practical application of these methods using PM2.5 mass concentration data from two industrial sites in Thailand, confirming their effectiveness in real-world scenarios. Keywords: Log-normal distribution, Ratio of variances, Asymptotic confidence inter-val, Bootstrap confidence interval."]},{"key":"dc:title","label":"Title","values":["Confidence estimation of the ratio of variances of two log-normal populations"]}]}],"canonical_facts":{"dc:contributor.advisor":["Volodin, Andrei"],"dc:contributor.committeemember":["Sardarli, Arzu"],"dc:creator":["Tantikhajorngosol, Puttipong"],"dc:date.accessioned":["2026-06-08T20:16:09Z"],"dc:date.issued":["2025-07"],"dc:description":["A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Statistics, University of Regina. viii, 99 p."],"dc:description.abstract":["This study investigates asymptotic and bootstrap confidence intervals (CIs) for the ratio of variances of two independent log-normal distributions. Extensive simula-tions were conducted to evaluate the performance of these CIs under varying sample sizes (10 to 350) and variance ratios, with one variance fixed at 0.1 and the other varying from 0.1 to 2.0. The impacts of equal and unequal were studied. The results reveal that the asymptotic CI performs well for small variance differences, especially with moderate to large sample sizes, while bootstrap CIs outperform it for larger variance differences. Notably, the t-bootstrap CI excels when both the variance dif-ference and sample sizes are large, whereas the percentile and standard bootstrap CIs are preferable for small variance differences. The study also demonstrates the practical application of these methods using PM2.5 mass concentration data from two industrial sites in Thailand, confirming their effectiveness in real-world scenarios. Keywords: Log-normal distribution, Ratio of variances, Asymptotic confidence inter-val, Bootstrap confidence interval."],"dc:identifier.doi":["https://doi.org/10.82465/161"],"dc:identifier.uri":["https://hdl.handle.net/10294/17141"],"dc:language.iso":["en"],"dc:publisher":["Faculty of Graduate Studies and Research, University of Regina"],"dc:title":["Confidence estimation of the ratio of variances of two log-normal populations"],"dc:type":["master thesis"],"thesis:degree_discipline":["Statistics"],"thesis:degree_name":["Master of Science (MSc)"],"thesis:institution_name":["University of Regina"]},"updated_at":"2026-07-24T04:03:32Z"}