{"id":{"repo_id":"etsu","oai_identifier":"oai:dc.etsu.edu:etd-2187"},"canonical_url":"https://search.dev.ndltd.org/etd/etsu/oai:dc.etsu.edu:etd-2187","repository":{"repo_id":"etsu","name":"East Tennessee State University","base_url":"https://dc.etsu.edu/do/oai/"},"display":{"title":"The Interquartile Range: Theory and Estimation.","abstract":"<p>The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, <b><em>IQR</em> = <em>Q</em><sub>3</sub> - <em>Q</em><sub>1</sub></b>. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.</p>","abstract_html":"&lt;p&gt;The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, &lt;b&gt;&lt;em&gt;IQR&lt;/em&gt; = &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;3&lt;/sub&gt; - &lt;em&gt;Q&lt;/em&gt;&lt;sub&gt;1&lt;/sub&gt;&lt;/b&gt;. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.&lt;/p&gt;","abstract_has_math":false,"creators":["Whaley, Dewey Lonzo"],"institution":null,"degree_name":"MS (Master of Science)","degree_level":"Thesis - unrestricted","degree_discipline":"Mathematical Sciences","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2005,"date_issued":"2005-08-16T07:00:00Z","date_published":"2005-08-16T07:00:00Z","updated_at":"2026-07-24T02:19:43Z","subjects":["interquartile range","probability distribution","order statistics","bootstrapping","Applied Mathematics","Numerical Analysis and Computation","Physical Sciences and Mathematics","Statistics and Probability"],"languages":[],"rights":["Copyright by the authors."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.etsu.edu/etd/1030","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Whaley, Dewey Lonzo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2005-08-16T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - unrestricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS (Master of Science)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["interquartile range","probability distribution","order statistics","bootstrapping","Applied Mathematics","Numerical Analysis and Computation","Physical Sciences and Mathematics","Statistics and Probability"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Copyright by the authors."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.etsu.edu/context/etd/article/2187/viewcontent/WhaleyD052905f.pdf","https://dc.etsu.edu/etd/1030"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, <b><em>IQR</em> = <em>Q</em><sub>3</sub> - <em>Q</em><sub>1</sub></b>. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.</p>"]},{"key":"dc:title","label":"Title","values":["The Interquartile Range: Theory and Estimation."]}]}],"canonical_facts":{"dc:creator":["Whaley, Dewey Lonzo"],"dc:date.issued":["2005-08-16T07:00:00Z"],"dc:description.abstract":["<p>The interquartile range (IQR) is used to describe the spread of a distribution. In an introductory statistics course, the IQR might be introduced as simply the “range within which the middle half of the data points lie.” In other words, it is the distance between the two quartiles, <b><em>IQR</em> = <em>Q</em><sub>3</sub> - <em>Q</em><sub>1</sub></b>. We will compute the population IQR, the expected value, and the variance of the sample IQR for various continuous distributions. In addition, a bootstrap confidence interval for the population IQR will be evaluated.</p>"],"dc:identifier":["https://dc.etsu.edu/context/etd/article/2187/viewcontent/WhaleyD052905f.pdf","https://dc.etsu.edu/etd/1030"],"dc:rights":["Copyright by the authors."],"dc:subject":["interquartile range","probability distribution","order statistics","bootstrapping","Applied Mathematics","Numerical Analysis and Computation","Physical Sciences and Mathematics","Statistics and Probability"],"dc:title":["The Interquartile Range: Theory and Estimation."],"thesis:degree_discipline":["Mathematical Sciences"],"thesis:degree_level":["Thesis - unrestricted"],"thesis:degree_name":["MS (Master of Science)"]},"updated_at":"2026-07-24T02:19:43Z"}