a’dan<\/em> b’ye<\/em> kadar bir aral\u0131kta x 1<\/sub> ile x 2<\/sub> aras\u0131nda bir de\u011fer elde etme olas\u0131l\u0131\u011f\u0131 a\u015fa\u011f\u0131daki form\u00fcl kullan\u0131larak bulunabilir:<\/span><\/p>\n P(x 1<\/sub> ile x 2<\/sub> aras\u0131nda bir de\u011fer elde edin) = (x 2<\/sub> \u2013 x 1<\/sub> ) \/ (b \u2013 a)<\/span> <\/p>\n Python’da tekd\u00fcze da\u011f\u0131l\u0131mla ilgili olas\u0131l\u0131klar\u0131 hesaplamak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanan scipy.stats.uniform()<\/a> i\u015flevini kullanabiliriz:<\/span><\/p>\n scipy.stats.uniform(x, loc, \u00f6l\u00e7ek)<\/span><\/strong><\/p>\n Alt\u0131n:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n Her 20 dakikada bir otob\u00fcs dura\u011f\u0131na bir otob\u00fcs\u00fcn geldi\u011fini varsayal\u0131m. Otob\u00fcs dura\u011f\u0131na vard\u0131\u011f\u0131n\u0131zda otob\u00fcs\u00fcn 8 dakika veya daha k\u0131sa s\u00fcrede gelme olas\u0131l\u0131\u011f\u0131 nedir?<\/span><\/p>\n Bu olas\u0131l\u0131\u011f\u0131 hesaplamak i\u00e7in Python’da a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Otob\u00fcs\u00fcn 8 dakika veya daha k\u0131sa s\u00fcrede gelme olas\u0131l\u0131\u011f\u0131 0,4’t\u00fcr<\/strong> .<\/span><\/p>\n Belirli bir kurba\u011fa t\u00fcr\u00fcn\u00fcn a\u011f\u0131rl\u0131\u011f\u0131 15 ila 25 gram aras\u0131nda e\u015fit olarak da\u011f\u0131lm\u0131\u015ft\u0131r. Rastgele bir kurba\u011fa se\u00e7erseniz a\u011f\u0131rl\u0131\u011f\u0131n\u0131n 17 ile 19 gram aras\u0131nda olma olas\u0131l\u0131\u011f\u0131 nedir?<\/span><\/p>\n Bu olas\u0131l\u0131\u011f\u0131 hesaplamak i\u00e7in Python’da a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Kurba\u011fan\u0131n a\u011f\u0131rl\u0131\u011f\u0131n\u0131n 17 ile 19 gram aras\u0131nda olma olas\u0131l\u0131\u011f\u0131 0,2’dir<\/strong> .<\/span><\/p>\n Bir NBA ma\u00e7\u0131n\u0131n s\u00fcresi 120 ila 170 dakika aras\u0131nda e\u015fit olarak da\u011f\u0131t\u0131l\u0131r. Rastgele se\u00e7ilen bir NBA ma\u00e7\u0131n\u0131n 150 dakikadan fazla s\u00fcrme olas\u0131l\u0131\u011f\u0131 nedir?<\/span><\/p>\n Bu olas\u0131l\u0131\u011f\u0131 hesaplamak i\u00e7in Python’da a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n Rastgele se\u00e7ilen bir NBA ma\u00e7\u0131n\u0131n 150 dakikadan fazla s\u00fcrme olas\u0131l\u0131\u011f\u0131 0,4’t\u00fcr<\/strong> .<\/span><\/p>\n Bonus:<\/strong> Tekd\u00fczen Da\u011f\u0131t\u0131m Hesaplay\u0131c\u0131s\u0131n\u0131 kullanarak her \u00f6rne\u011fin \u00e7\u00f6z\u00fcm\u00fcn\u00fc kontrol edebilirsiniz.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer yayg\u0131n da\u011f\u0131t\u0131mlar\u0131n nas\u0131l kullan\u0131laca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Python’da Binom Da\u011f\u0131l\u0131m\u0131 Nas\u0131l Kullan\u0131l\u0131r<\/a> D\u00fczg\u00fcn da\u011f\u0131l\u0131m, a’dan b’ye kadar olan aral\u0131ktaki her de\u011ferin ayn\u0131 se\u00e7ilme olas\u0131l\u0131\u011f\u0131na sahip oldu\u011fu bir olas\u0131l\u0131k da\u011f\u0131l\u0131m\u0131d\u0131r. a’dan b’ye kadar bir aral\u0131kta x 1 ile x 2 aras\u0131nda bir de\u011fer elde etme olas\u0131l\u0131\u011f\u0131 a\u015fa\u011f\u0131daki form\u00fcl kullan\u0131larak bulunabilir: P(x 1 ile x 2 aras\u0131nda bir de\u011fer elde edin) = (x 2 \u2013 x 1 ) \/ […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2496","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n![\"Tekd\u00fcze](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/uniforme_pic.jpg\")
<\/p>\n\n
\u00f6rnek 1<\/strong><\/span><\/h3>\n
from<\/span> scipy. stats<\/span> import<\/span> uniform\n\n#calculate uniform probability\n<\/span>uniform. cdf<\/span> (x=8, loc=0, scale=20) - uniform. cdf<\/span> (x=0, loc=0, scale=20)\n\n0.4<\/strong><\/pre>\n \u00d6rnek 2<\/strong><\/span><\/h3>\n
from<\/span> scipy. stats<\/span> import<\/span> uniform\n\n#calculate uniform probability\n<\/span>uniform. cdf<\/span> (x=19, loc=15, scale=10) - uniform. cdf<\/span> (x=17, loc=15, scale=10)\n\n0.2<\/strong><\/pre>\n \u00d6rnek 3<\/strong><\/span><\/h3>\n
from scipy. stats<\/span> import<\/span> uniform<\/span>\n\n#calculate uniform probability \nuniform. cdf<\/span> (x=170, loc=120, scale=50) - uniform. cdf<\/span> (x=150, loc=120, scale=50)\n\n0.4<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Python’da Poisson da\u011f\u0131l\u0131m\u0131 nas\u0131l kullan\u0131l\u0131r?<\/a>
Python’da t da\u011f\u0131t\u0131m\u0131 nas\u0131l kullan\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"