Bu, basit bir do\u011frusal regresyon modelindeki<\/a> regresyon katsay\u0131s\u0131na verilen ad olan eski “regresyon katsay\u0131s\u0131” ile \u00e7eli\u015fir.<\/span><\/p>\n K\u0131smi regresyon katsay\u0131s\u0131n\u0131 yorumlaman\u0131n yolu \u015fu \u015fekildedir: Di\u011fer t\u00fcm yorday\u0131c\u0131 de\u011fi\u015fkenlerin sabit kald\u0131\u011f\u0131 varsay\u0131larak, belirli bir yorday\u0131c\u0131 de\u011fi\u015fkendeki bir birimlik art\u0131\u015fla ili\u015fkili yan\u0131t<\/a> de\u011fi\u015fkenindeki ortalama de\u011fi\u015fiklik.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, \u00e7oklu do\u011frusal regresyon modelinde k\u0131smi regresyon katsay\u0131lar\u0131n\u0131n nas\u0131l tan\u0131mlanaca\u011f\u0131n\u0131 ve yorumlanaca\u011f\u0131n\u0131 a\u00e7\u0131klamaktad\u0131r.<\/span><\/p>\n Diyelim ki, ders \u00e7al\u0131\u015fmak i\u00e7in harcanan saatlerin ve al\u0131nan haz\u0131rl\u0131k s\u0131navlar\u0131n\u0131n say\u0131s\u0131n\u0131n, bir \u00f6\u011frencinin belirli bir \u00fcniversiteye giri\u015f s\u0131nav\u0131nda ald\u0131\u011f\u0131 notu etkileyip etkilemedi\u011fini bilmek istiyoruz.<\/span><\/p>\n Bu ili\u015fkiyi ara\u015ft\u0131rmak i\u00e7in, \u00e7al\u0131\u015f\u0131lan saatleri<\/strong> ve girilen haz\u0131rl\u0131k s\u0131navlar\u0131n\u0131<\/strong> yorday\u0131c\u0131 de\u011fi\u015fkenler olarak ve s\u0131nav puanlar\u0131n\u0131<\/strong> yan\u0131t de\u011fi\u015fkeni olarak kullanarak \u00e7oklu do\u011frusal regresyon modelini yerle\u015ftirebiliriz.<\/span><\/p>\n A\u015fa\u011f\u0131daki regresyon tablosu modelin sonucunu g\u00f6stermektedir:<\/span> <\/p>\n K\u0131smi regresyon katsay\u0131lar\u0131n\u0131 \u015fu \u015fekilde yorumlayabilirsiniz:<\/span><\/p>\n Saat:<\/strong> Deneme s\u0131navlar\u0131n\u0131n say\u0131s\u0131n\u0131n sabit kald\u0131\u011f\u0131 varsay\u0131ld\u0131\u011f\u0131nda, ders \u00e7al\u0131\u015fmak i\u00e7in harcanan her ek saat i\u00e7in s\u0131nav puan\u0131 ortalama 5,56<\/strong> puan artar.<\/span><\/p>\n Buna ba\u015fka bir a\u00e7\u0131dan da bakabiliriz: \u00d6\u011frenci A ve \u00d6\u011frenci B ayn\u0131 say\u0131da haz\u0131rl\u0131k s\u0131nav\u0131na girerse ancak \u00d6\u011frenci A bir saat daha uzun \u00e7al\u0131\u015f\u0131rsa, \u00d6\u011frenci A, \u00d6\u011frenci B’den 5,56 puan daha y\u00fcksek puan almal\u0131d\u0131r.<\/span><\/p>\n Haz\u0131rl\u0131k S\u0131navlar\u0131:<\/strong> \u00c7al\u0131\u015f\u0131lan saat say\u0131s\u0131n\u0131n sabit kald\u0131\u011f\u0131 varsay\u0131ld\u0131\u011f\u0131nda, al\u0131nan her ek haz\u0131rl\u0131k s\u0131nav\u0131 i\u00e7in s\u0131nav puan\u0131 ortalama 0,60<\/strong> puan azal\u0131r.<\/span><\/p>\n Ba\u015fka bir deyi\u015fle, e\u011fer hem A \u00f6\u011frencisi hem de B \u00f6\u011frencisi ayn\u0131 say\u0131da ders \u00e7al\u0131\u015f\u0131yorsa ancak A \u00f6\u011frencisi ek bir haz\u0131rl\u0131k s\u0131nav\u0131na giriyorsa, A \u00f6\u011frencisi B \u00f6\u011frencisinin puan\u0131ndan 0,60 puan daha d\u00fc\u015f\u00fck bir puan almal\u0131d\u0131r.<\/span><\/p>\n Regresyon sonucundaki katsay\u0131lar\u0131 kullanarak tahmin edilen \u00e7oklu do\u011frusal regresyon denklemini yazabiliriz:<\/span><\/p>\n S\u0131nav puan\u0131 = 67,67 + 5,56*(saat) \u2013 0,60*(haz\u0131rl\u0131k s\u0131navlar\u0131)<\/span><\/p>\n Bu tahmini regresyon denklemini, bir \u00f6\u011frencinin \u00e7al\u0131\u015fma saati ve girdi\u011fi deneme s\u0131navlar\u0131n\u0131n say\u0131s\u0131na ba\u011fl\u0131 olarak beklenen s\u0131nav puan\u0131n\u0131 hesaplamak i\u00e7in kullanabiliriz.<\/span><\/p>\n \u00d6rne\u011fin \u00fc\u00e7 saat \u00e7al\u0131\u015f\u0131p haz\u0131rl\u0131k s\u0131nav\u0131na giren bir \u00f6\u011frencinin notunun 83,75<\/strong> olmas\u0131 gerekir:<\/span><\/p>\n S\u0131nav puan\u0131 = 67,67 + 5,56*(3) \u2013 0,60*(1) = 83,75<\/span><\/p>\n Basit Do\u011frusal Regresyona Giri\u015f<\/a> K\u0131smi regresyon katsay\u0131s\u0131, \u00e7oklu do\u011frusal regresyon modelindeki regresyon katsay\u0131lar\u0131na verilen add\u0131r. Bu, basit bir do\u011frusal regresyon modelindeki regresyon katsay\u0131s\u0131na verilen ad olan eski “regresyon katsay\u0131s\u0131” ile \u00e7eli\u015fir. K\u0131smi regresyon katsay\u0131s\u0131n\u0131 yorumlaman\u0131n yolu \u015fu \u015fekildedir: Di\u011fer t\u00fcm yorday\u0131c\u0131 de\u011fi\u015fkenlerin sabit kald\u0131\u011f\u0131 varsay\u0131larak, belirli bir yorday\u0131c\u0131 de\u011fi\u015fkendeki bir birimlik art\u0131\u015fla ili\u015fkili yan\u0131t de\u011fi\u015fkenindeki ortalama de\u011fi\u015fiklik. A\u015fa\u011f\u0131daki \u00f6rnek, […]<\/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-1571","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: K\u0131smi regresyon katsay\u0131lar\u0131n\u0131n yorumlanmas\u0131<\/strong><\/span><\/h3>\n
![\"K\u0131smi](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/multipleregexcel4.png\")
<\/p>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
\u00c7oklu Do\u011frusal Regresyona Giri\u015f<\/a>
Regresyon Tablosu Nas\u0131l Okunmal\u0131 ve Yorumlanmal\u0131<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"