{"id":205644,"date":"2025-03-25T06:54:11","date_gmt":"2025-03-25T06:54:11","guid":{"rendered":"https:\/\/learnexams.com\/blog\/?p=205644"},"modified":"2025-03-25T06:54:13","modified_gmt":"2025-03-25T06:54:13","slug":"you-use-the-finite-population-correction-factor-when","status":"publish","type":"post","link":"https:\/\/www.learnexams.com\/blog\/2025\/03\/25\/you-use-the-finite-population-correction-factor-when\/","title":{"rendered":"You use the finite population correction factor when"},"content":{"rendered":"\n<p>You use the finite population correction factor when<\/p>\n\n\n\n<p>A) you sample without replacement and the sample size is larger than 5% of the population size.<\/p>\n\n\n\n<p>B) you sample without replacement and the sample size is smaller than 5% of the population size.<\/p>\n\n\n\n<p>C) you sample with replacement and the sample size is larger than 5% of the population size.<\/p>\n\n\n\n<p>D) you sample with replacement and the sample size is smaller than 5% of the population size.<\/p>\n\n\n\n<p><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-ast-global-color-6-color\"><strong>The correct answer and explanation is :<\/strong><\/mark><\/p>\n\n\n\n<p>The correct answer is:<\/p>\n\n\n\n<p><strong>A) You sample without replacement and the sample size is larger than 5% of the population size.<\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Explanation:<\/h3>\n\n\n\n<p>The <strong>finite population correction (FPC) factor<\/strong> is used to adjust the standard error of a sample statistic when sampling is done <strong>without replacement<\/strong> from a finite population. This correction accounts for the reduction in variability due to a relatively large sample size in comparison to the total population.<\/p>\n\n\n\n<p>The FPC factor is applied when the sample size, <strong>n<\/strong>, is more than <strong>5% of the total population size, N<\/strong> (i.e., <strong>n\/N &gt; 0.05<\/strong>). The formula for the correction factor is:<\/p>\n\n\n\n<p>[<br>FPC = \\sqrt{\\frac{N &#8211; n}{N &#8211; 1}}<br>]<\/p>\n\n\n\n<p>This correction is necessary because when a sample is drawn <strong>without replacement<\/strong>, each selection reduces the number of remaining elements, affecting the overall variability. When the sample size is small compared to the population (less than 5%), the effect of this reduction is negligible, and the standard error remains nearly the same as in infinite population scenarios.<\/p>\n\n\n\n<p>However, when the sample size is relatively <strong>large<\/strong> (greater than 5% of the population), failing to apply the FPC would overestimate the standard error, leading to unnecessary caution in statistical inference.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Why Other Options Are Incorrect:<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>B) Incorrect<\/strong>: The correction is not needed when the sample size is small (less than 5%) because its effect on the variability is minimal.<\/li>\n\n\n\n<li><strong>C) Incorrect<\/strong>: When sampling <strong>with replacement<\/strong>, each draw is independent, and the population size does not impact the variance, so no correction is needed.<\/li>\n\n\n\n<li><strong>D) Incorrect<\/strong>: Similar to (C), with replacement sampling does not require the FPC factor.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><img decoding=\"async\" src=\"https:\/\/learnexams.com\/blog\/wp-content\/uploads\/2025\/03\/image-1373.png\" alt=\"\" class=\"wp-image-205645\"\/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>You use the finite population correction factor when A) you sample without replacement and the sample size is larger than 5% of the population size. B) you sample without replacement and the sample size is smaller than 5% of the population size. C) you sample with replacement and the sample size is larger than 5% [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[25],"tags":[],"class_list":["post-205644","post","type-post","status-publish","format-standard","hentry","category-exams-certification"],"_links":{"self":[{"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/posts\/205644","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/comments?post=205644"}],"version-history":[{"count":0,"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/posts\/205644\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/media?parent=205644"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/categories?post=205644"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.learnexams.com\/blog\/wp-json\/wp\/v2\/tags?post=205644"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}