{"id":191,"date":"2007-01-17T11:22:04","date_gmt":"2007-01-17T10:22:04","guid":{"rendered":"http:\/\/www.decisionsciencenews.com\/?p=191"},"modified":"2007-01-17T11:27:45","modified_gmt":"2007-01-17T10:27:45","slug":"pepys-problem-solved","status":"publish","type":"post","link":"https:\/\/www.decisionsciencenews.com\/?p=191","title":{"rendered":"Pepys&#8217; Problem Solved"},"content":{"rendered":"<p>A CHANGE OF WEIGHT REVEALS NEWTON&#8217;S FLAW<\/p>\n<div style=\"text-align: center\"><img decoding=\"async\" id=\"image190\" alt=\"dce.jpg\" src=\"http:\/\/www.decisionsciencenews.com\/wp-content\/uploads\/2007\/01\/dce.jpg\" \/><\/div>\n<p>Interestingly, Newton&#8217;s enumerated solution to Pepys&#8217; problem is correct (see previous DSN entry), but the logic is wrong, as Statistician Stephen Stigler points out.<\/p>\n<p>The problem is now solved by with bionomial distribution: the probability of A is the greatest. For those who <a href=\"http:\/\/www.r-project.org\/\">speak R<\/a>, the probabilities are<\/p>\n<p>Probability of Event A = sum(dbinom(1:6,6,1\/6)) = 0.67<br \/>\nProbability of Event B = sum(dbinom(2:12,12,1\/6)) = 0.62<br \/>\nProbability of Event C = sum(dbinom(3:18,18,1\/6)) = 0.60<\/p>\n<p>This was Newton&#8217;s logic:<\/p>\n<p>&#8220;If the question be thus stated, it appears by an easy computation that the expectation of A is greater than that of B or C; that is, the task of A is the easiest. And the reason is because A has all the chances of sixes on his dyes for his expectation, but B and C have not all the chances on theirs. For when B throws a single six or C but one or two sixes, they miss of their expectations.&#8221;<\/p>\n<p>But Stigler points out Newton&#8217;s logic doesn&#8217;t hold if we use loaded dice, in which the probability of a six is not 1\/6 but 1\/4.<\/p>\n<p>Probability of Event A&#8217; = sum(dbinom(1:6,6,1\/4)) = 0.82<br \/>\nProbability of Event B&#8217; = sum(dbinom(2:12,12,1\/4)) = 0.84<br \/>\nProbability of Event C&#8217; = sum(dbinom(3:18,18,1\/4))= 0.86<\/p>\n<p>Mathemagically, the probabilities grow from A to C in this case.<\/p>\n<p>For a fun and short read, check out:<\/p>\n<p>Stigler, Stephen M. (2006). Isaac Newton as a Probabilist. <em>Statistical Science, 21(3)<\/em>, 400-403. [<a target=\"_blank\" href=\"http:\/\/arxiv.org\/PS_cache\/math\/pdf\/0701\/0701089.pdf\">Download<\/a>]<br \/>\n<font size=\"1\"><font size=\"1\"><font size=\"1\"> <\/font><font size=\"1\"><font size=\"1\">Photo credit: http:\/\/www.flickr.com\/photos\/awshots\/352212946\/ <\/font><\/font> <\/font> <\/font><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A CHANGE OF WEIGHT REVEALS NEWTON&#8217;S FLAW Interestingly, Newton&#8217;s enumerated solution to Pepys&#8217; problem is correct (see previous DSN entry), but the logic is wrong, as Statistician Stephen Stigler points out. The problem is now solved by with bionomial distribution: the probability of A is the greatest. For those who speak R, the probabilities are [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[4,2],"tags":[],"class_list":["post-191","post","type-post","status-publish","format-standard","hentry","category-encyclopedia","category-research-news"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4LKj-35","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/191","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=191"}],"version-history":[{"count":0,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/191\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=191"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=191"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=191"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}