Bu \u00f6rnek, x=10 i\u00e7in, alpha=8 ve beta=2 parametrelerine sahip gamma da\u011f\u0131l\u0131m\u0131n\u0131n k\u00fcm\u00fclatif da\u011f\u0131l\u0131m de\u011ferini hesaplar.<\/p>\n Bir m\u00fchendislik par\u00e7as\u0131n\u0131n \u00f6m\u00fcr s\u00fcresini gamma da\u011f\u0131l\u0131m\u0131yla modellemekteyiz. \u015eekil parametresi (alpha) 9 ve \u00f6l\u00e7ek parametresi (beta) 3 olan bir par\u00e7an\u0131n, en az 20 y\u0131l dayanma olas\u0131l\u0131\u011f\u0131n\u0131 hesaplayal\u0131m:<\/p>\n Bu hesaplama, par\u00e7an\u0131n 20 y\u0131l veya daha fazla dayanma olas\u0131l\u0131\u011f\u0131n\u0131 k\u00fcm\u00fclatif olarak g\u00f6sterir. 20 y\u0131l i\u00e7inde ba\u015far\u0131s\u0131z olma olas\u0131l\u0131\u011f\u0131 GAMMA.DIST kullan\u0131larak hesaplan\u0131r ve ard\u0131ndan bu de\u011ferin 1’den \u00e7\u0131kart\u0131lmas\u0131yla 20 y\u0131l veya daha fazla dayanma olas\u0131l\u0131\u011f\u0131 bulunur.<\/p>\n Bir restoran\u0131n yemek servis s\u00fcresini gamma da\u011f\u0131l\u0131m\u0131 kullanarak modelledi\u011fini d\u00fc\u015f\u00fcnelim. Ortalama 15 dakika s\u00fcre ve 5 dakikal\u0131k bir \u00f6l\u00e7ek parametresiyle; bir m\u00fc\u015fterinin yemeklerini 10 dakika i\u00e7inde almas\u0131n\u0131n yo\u011funluk oran\u0131n\u0131 hesaplayal\u0131m:<\/p>\n Bu form\u00fcl, m\u00fc\u015fterinin yemeklerini tam olarak 10 dakika i\u00e7inde alma olas\u0131l\u0131\u011f\u0131n\u0131n yo\u011funlu\u011funu hesaplar. Burada kullan\u0131lan FALSE parametresi, yo\u011funluk fonksiyonunun kullan\u0131lmas\u0131n\u0131 sa\u011flar.<\/p>\n","protected":false},"excerpt":{"rendered":" Gama da\u011f\u0131l\u0131m\u0131n\u0131 verir<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[582],"tags":[],"class_list":["post-15433","post","type-post","status-publish","format-standard","hentry","category-istatistik"],"acf":[],"yoast_head":"\nGAMMA.DIST<\/code> fonksiyonu, belirli bir de\u011ferin, alfa ve beta parametreleriyle belirlenmi\u015f bir gamma da\u011f\u0131l\u0131m\u0131nda hangi k\u00fcm\u00fclatif da\u011f\u0131l\u0131m de\u011ferine veya olas\u0131l\u0131k yo\u011funlu\u011funa kar\u015f\u0131l\u0131k geldi\u011fini belirlemek i\u00e7in kullan\u0131l\u0131r. Excel ve Google Sheets’te bu fonksiyon, istatistik ve olas\u0131l\u0131k hesaplamalar\u0131nda, \u00f6zellkle ya\u015fam s\u00fcresi, bekleme s\u00fcreleri ve biyolojik s\u00fcre\u00e7lerin modellemesinde s\u0131kl\u0131kla tercih edilir.<\/p>\nS\u00f6zdizimi ve Parametreler<\/h2>\n
GAMMA.DIST(x, alpha, beta, cumulative)<\/code> fonksiyonunun s\u00f6zdizimi \u015fu \u015fekildedir:<\/p>\n\n
\u00d6rnek Kullan\u0131m<\/h2>\n
GAMMA.DIST(10, 8, 2, TRUE) <\/code> <\/pre>\nPratik G\u00f6revler<\/h2>\n
1. \u00d6m\u00fcr De\u011ferlendirmesi<\/h2>\n
=1 - GAMMA.DIST(20, 9, 3, TRUE) <\/code> <\/pre>\n2. H\u0131zl\u0131 Servis Analizi<\/h2>\n
GAMMA.DIST(10, 3, 5, FALSE) <\/code> <\/pre>\n