{"id":110,"date":"2018-07-03T18:51:42","date_gmt":"2018-07-03T18:51:42","guid":{"rendered":"https:\/\/orange-attractor.eu\/?p=110"},"modified":"2019-04-16T21:29:45","modified_gmt":"2019-04-16T21:29:45","slug":"the-limits-of-central-limit-theorem-part-2","status":"publish","type":"post","link":"https:\/\/orange-attractor.eu\/?p=110","title":{"rendered":"The limits of central limit theorem &#8211; part 2"},"content":{"rendered":"<p>In the <a href=\"?p=56\">previous part<\/a> we made look through the distribution of sample means for three distributions: Uniform, Cauchy, and Petersburg distribution. The Cauchy and Petersburg distributions do not fulfill the Central Limit Theorem since they have infinite variance (and infinite expected value in &#8220;Petersburg&#8221; case). Now we will have a look at the numerical results for standard deviation of sample means. As in previous part, we use Uniform distribution only as a reference since it fulfills CLT and we use the same pseud-random number generator (Mersenne-Twister).<\/p>\n<p><!--more--><\/p>\n<p>Uniform distribution, gives a really nice impressions when looking through the chart showing standard deviation \\(\\sigma\\) vs sample size \\(n\\):<\/p>\n<figure id=\"attachment_117\" aria-describedby=\"caption-attachment-117\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform.png\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform-1024x768.png\" alt=\"\" width=\"640\" height=\"480\" class=\"size-large wp-image-117\" srcset=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform-1024x768.png 1024w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform-300x225.png 300w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform-768x576.png 768w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform-220x165.png 220w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/uniform.png 1600w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-117\" class=\"wp-caption-text\">Standard deviation for distribution of sample means as a function of sample size<\/figcaption><\/figure>\n<p>It behaves as we expected &#8211; in accordance to the CLT &#8211; it varies like: \\(\\frac{1}{\\sqrt{n}}\\).<\/p>\n<p>And now &#8211; stars of our show &#8211; Cauchy distribution:<\/p>\n<figure id=\"attachment_120\" aria-describedby=\"caption-attachment-120\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy.png\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy-1024x768.png\" alt=\"\" width=\"640\" height=\"480\" class=\"size-large wp-image-120\" srcset=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy-1024x768.png 1024w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy-300x225.png 300w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy-768x576.png 768w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy-220x165.png 220w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/cauchy.png 1600w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-120\" class=\"wp-caption-text\">Standard deviation vs sample size for distribution fo sample means<\/figcaption><\/figure>\n<p>&#8230;and Petersburg distribution:<\/p>\n<figure id=\"attachment_121\" aria-describedby=\"caption-attachment-121\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg.png\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg-1024x768.png\" alt=\"\" width=\"640\" height=\"480\" class=\"size-large wp-image-121\" srcset=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg-1024x768.png 1024w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg-300x225.png 300w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg-768x576.png 768w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg-220x165.png 220w, https:\/\/orange-attractor.eu\/wp-content\/uploads\/2018\/07\/petersburg.png 1600w\" sizes=\"(max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-121\" class=\"wp-caption-text\">Standard deviation vs sample size for distribution of sample means<\/figcaption><\/figure>\n<p>In spite of trying many different pseudo-random generator seed values the result is the roughly the same &#8211; \\(\\sigma(n)\\) does not seem to converge.<\/p>\n<p>Conclusions: <\/p>\n<p>Since distributions of sample means for the Cauchy and Petersburg distributions do not fulfill the assumptions of CLT &#8211;  we didn&#8217;t expected the same result as in &#8220;properly behaving distributions&#8221; like uniform distribution. In spite we didn&#8217;t discover anything new with our &#8220;experimental statistics&#8221;, we he had a lot of fun and wanted to share it with you.<\/p>\n<p><i>Miko\u0142aj Sitarz, 2018<\/i><br \/>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/orange-attractor.eu\/wp-content\/uploads\/2019\/04\/cc-by-sa-nc.png\" alt=\"\" width=\"88\" height=\"31\" class=\"aligncenter size-full wp-image-240\" \/><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In the previous part we made look through the distribution of sample means for three distributions: Uniform, Cauchy, and Petersburg distribution. The Cauchy and Petersburg distributions do not fulfill the Central Limit Theorem since they have infinite variance (and infinite expected value in &#8220;Petersburg&#8221; case). Now we will have a look at the numerical results&hellip; <a class=\"read-more\" href=\"https:\/\/orange-attractor.eu\/?p=110\">Read More<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"image","meta":{"footnotes":""},"categories":[1],"tags":[5,4],"class_list":["post-110","post","type-post","status-publish","format-image","hentry","category-uncategorized","tag-clt","tag-statistics","post_format-post-format-image"],"_links":{"self":[{"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/posts\/110"}],"collection":[{"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=110"}],"version-history":[{"count":14,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/posts\/110\/revisions"}],"predecessor-version":[{"id":251,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=\/wp\/v2\/posts\/110\/revisions\/251"}],"wp:attachment":[{"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=110"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=110"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/orange-attractor.eu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=110"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}