{"id":10,"date":"2024-04-03T23:09:22","date_gmt":"2024-04-03T20:09:22","guid":{"rendered":"https:\/\/sisu.ut.ee\/measurement\/34-other-distribution-functions-rectangular-and-triangular-distribution\/"},"modified":"2024-06-19T15:42:42","modified_gmt":"2024-06-19T12:42:42","slug":"34-other-distribution-functions-rectangular-and-triangular-distribution","status":"publish","type":"page","link":"https:\/\/sisu.ut.ee\/measurement\/34-other-distribution-functions-rectangular-and-triangular-distribution\/","title":{"rendered":"3.5. Rectangular and triangular distribution"},"content":{"rendered":"<p><strong>Brief summary:<\/strong> <strong>Rectangular distribution<\/strong> and <strong>triangular distribution<\/strong> are explained, as well as how the uncertainties corresponding to rectangular or triangular distribution can be converted to standard uncertainties. Often the information on distribution function is missing and then usually some distribution function is assumed or postulated. Rectangular and triangular distributions are among the most common postulated distribution functions. Recommendations are given, which of these distributions to assume.<\/p>\n<p style=\"text-align: center;\"><\/p><div class=\"ratio ratio-16x9 mb-3\"><div class=\"video-placeholder-wrapper video-placeholder-wrapper--16x9\">\n\t\t\t    <div class=\"video-placeholder d-flex justify-content-center align-items-center\">\n\t\t\t        <div class=\"overlay text-white p-2 w-100 text-center d-block justify-content-center align-items-center\">\n\t\t\t            <div>To view third-party content, please accept cookies.<\/div>\n\t\t\t            <button class=\"btn btn-secondary btn-sm mt-1 consent-change\">Change consent<\/button>\n\t\t\t        <\/div>\n\t\t\t    <\/div>\n\t\t\t<\/div>\n<\/div>\n<h4 style=\"text-align: center;\"><strong>Other distribution functions: rectangular and triangular distribution<br>\n<\/strong><a style=\"line-height: 1.6em;\" href=\"http:\/\/www.uttv.ee\/naita?id=17584\" target=\"_blank\" rel=\"noopener\">http:\/\/www.uttv.ee\/naita?id=17584<\/a><\/h4>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.youtube.com\/watch?v=g_PefybO2Ao\" target=\"_blank\" rel=\"noopener\">https:\/\/www.youtube.com\/watch?v=g_PefybO2Ao<\/a><\/p>\n<p style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" width=\"587\" height=\"403\" class=\"alignnone wp-image-277\" title=\"3-5-skeem1.png\" src=\"https:\/\/sisu.ut.ee\/wp-content\/uploads\/sites\/18\/3-5-skeem1.png\" alt=\"3-5-skeem1.png\" srcset=\"https:\/\/sisu.ut.ee\/wp-content\/uploads\/sites\/18\/3-5-skeem1.png 587w, https:\/\/sisu.ut.ee\/wp-content\/uploads\/sites\/18\/3-5-skeem1-300x206.png 300w\" sizes=\"auto, (max-width: 587px) 100vw, 587px\"><\/p>\n<p style=\"text-align: center;\"><strong>Scheme 3.3.\u00a0Rectangular and triangular distributions. Both of them correspond to the situation (10.000 \u00b1 0.063) ml.<\/strong><\/p>\n<p style=\"text-align: left;\"><span style=\"line-height: 1.6em;\">In measurement uncertainty estimation situations often occur where it is necessary to make choice between two alternatives of which one may possibly lead to somewhat overestimated uncertainty and the other one to somewhat underestimated uncertainty. In such situation it is usually reasonable to rather somewhat overestimate than underestimate the uncertainty.<\/span><\/p>\n<p><a href=\"https:\/\/sisu.ut.ee\/measurement\/self-test-3-5\/\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-60\" style=\"margin-right: auto; margin-left: auto;\" title=\"selftest.png\" src=\"https:\/\/sisu.ut.ee\/wp-content\/uploads\/sites\/18\/selftest.png\" alt=\"selftest.png\" width=\"104\" height=\"41\"><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Brief summary: Rectangular distribution and triangular distribution are explained, as well as how the uncertainties corresponding to rectangular or triangular distribution can be converted to standard uncertainties. Often the information on distribution function is missing and then usually some distribution &#8230;<\/p>\n","protected":false},"author":14,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"class_list":["post-10","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/pages\/10","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/comments?post=10"}],"version-history":[{"count":2,"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/pages\/10\/revisions"}],"predecessor-version":[{"id":663,"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/pages\/10\/revisions\/663"}],"wp:attachment":[{"href":"https:\/\/sisu.ut.ee\/measurement\/wp-json\/wp\/v2\/media?parent=10"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}