{"id":543,"date":"2023-07-29T13:49:52","date_gmt":"2023-07-29T13:49:52","guid":{"rendered":"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/"},"modified":"2023-07-29T13:49:52","modified_gmt":"2023-07-29T13:49:52","slug":"regresyon-katsayilari-nasil-yorumlanir","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/","title":{"rendered":"Regresyon katsay\u0131lar\u0131 nas\u0131l yorumlan\u0131r?"},"content":{"rendered":"

<\/p>\n

\n

\u0130statistikte<\/span>regresyon analizi<\/span><\/a> , yorday\u0131c\u0131 de\u011fi\u015fkenler ile bir yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fkiyi analiz etmek i\u00e7in kullan\u0131labilecek bir tekniktir.<\/span><\/p>\n

Regresyon analizini ger\u00e7ekle\u015ftirmek i\u00e7in yaz\u0131l\u0131m ( R , Stata , SPSS vb.) kulland\u0131\u011f\u0131n\u0131zda, regresyon sonu\u00e7lar\u0131n\u0131 \u00f6zetleyen bir regresyon tablosunu \u00e7\u0131kt\u0131 olarak alacaks\u0131n\u0131z.<\/span><\/p>\n

Regresyon tablosu sonucundaki en \u00f6nemli say\u0131lar muhtemelen regresyon katsay\u0131lar\u0131d\u0131r<\/strong> . Ancak \u00f6nemlerine ra\u011fmen bir\u00e7ok ki\u015fi bu say\u0131lar\u0131 do\u011fru \u015fekilde yorumlamakta zorluk \u00e7ekiyor.<\/span><\/p>\n

Bu e\u011fitimde bir regresyon analizi \u00f6rne\u011fi sunulur ve regresyondan kaynaklanan regresyon katsay\u0131lar\u0131n\u0131n nas\u0131l yorumlanaca\u011f\u0131na ili\u015fkin ayr\u0131nt\u0131l\u0131 bir a\u00e7\u0131klama sa\u011flan\u0131r.<\/span><\/p>\n

\u0130lgili:<\/strong> Regresyon Tablosunun Tamam\u0131n\u0131 Okuma ve Yorumlama<\/span><\/p>\n

Regresyon analizi \u00f6rne\u011fi<\/strong><\/span><\/h2>\n

A\u015fa\u011f\u0131daki de\u011fi\u015fkenleri kullanarak<\/span> bir regresyon analizi yapmak istedi\u011fimizi varsayal\u0131m<\/span> :<\/p>\n

Tahmini de\u011fi\u015fkenler<\/strong><\/span><\/p>\n

    \n
  • Toplam \u00e7al\u0131\u015f\u0131lan saat say\u0131s\u0131 ( s\u00fcrekli de\u011fi\u015fken \u2013 0 ile 20 aras\u0131nda<\/em> )<\/span><\/li>\n
  • \u00d6\u011frencinin \u00f6zel \u00f6\u011fretmen kullan\u0131p kullanmad\u0131\u011f\u0131 ( kategorik de\u011fi\u015fken \u2013 \u201cevet\u201d veya \u201chay\u0131r\u201d<\/em> )<\/span><\/li>\n<\/ul>\n

    Yan\u0131t de\u011fi\u015fkeni<\/strong><\/span><\/p>\n

      \n
    • S\u0131nav puan\u0131 ( s\u00fcrekli<\/em> de\u011fi\u015fken \u2013 1 ile 100 aras\u0131nda<\/em> )<\/span><\/li>\n<\/ul>\n

      \u00c7al\u0131\u015f\u0131lan saatlerin ve bir \u00f6\u011frencinin \u00f6zel \u00f6\u011fretmen kullan\u0131p kullanmamas\u0131n\u0131n s\u0131nav notu \u00fczerinde ger\u00e7ekten \u00f6nemli bir etkisi olup olmad\u0131\u011f\u0131n\u0131 g\u00f6rmek i\u00e7in yorday\u0131c\u0131 de\u011fi\u015fkenler ile yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fkiyi incelemek istiyoruz.<\/span><\/p>\n

      Bir regresyon analizi yapt\u0131\u011f\u0131m\u0131z\u0131 ve a\u015fa\u011f\u0131daki sonucu elde etti\u011fimizi varsayal\u0131m:<\/span><\/p>\n\n\n\n\n\n\n
      Terim<\/span><\/th>\n Katsay\u0131<\/span><\/th>\n Standart hata<\/span><\/th>\n \u0130statistikler<\/span><\/th>\n P de\u011feri<\/span><\/th>\n<\/tr>\n
      Tutmak<\/span><\/strong><\/td>\n 48.56<\/span><\/td>\n 14:32.<\/span><\/td>\n 3.39<\/span><\/td>\n 0,002<\/span><\/td>\n<\/tr>\n
      \u00c7al\u0131\u015f\u0131lan saatler<\/strong><\/span><\/td>\n 2.03<\/span><\/td>\n 0,67<\/span><\/td>\n 3.03<\/span><\/td>\n 0,009<\/span><\/td>\n<\/tr>\n
      \u00d6zel \u00f6\u011fretmen<\/span><\/strong><\/td>\n 8.34<\/span><\/td>\n 5.68<\/span><\/td>\n 1.47<\/span><\/td>\n 0,138<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      Her bir regresyon katsay\u0131s\u0131n\u0131n nas\u0131l yorumlanaca\u011f\u0131n\u0131 g\u00f6relim.<\/span><\/p>\n

      M\u00fcdahalenin yorumlanmas\u0131<\/strong><\/span><\/h2>\n

      Bir regresyon tablosundaki orijinal<\/strong> terim bize, t\u00fcm yorday\u0131c\u0131 de\u011fi\u015fkenler s\u0131f\u0131ra e\u015fit oldu\u011funda yan\u0131t de\u011fi\u015fkeni i\u00e7in beklenen ortalama de\u011feri s\u00f6yler.<\/span><\/p>\n

      Bu \u00f6rnekte orijin i\u00e7in regresyon katsay\u0131s\u0131 48,56’ya<\/strong> e\u015fittir. Bu, s\u0131f\u0131r saat \u00e7al\u0131\u015fan ( \u00c7al\u0131\u015f\u0131lan saat = 0)<\/em> ve \u00f6zel \u00f6\u011fretmen kullanmayan ( \u00d6\u011fretmen = 0)<\/em> bir \u00f6\u011frenci i\u00e7in beklenen ortalama s\u0131nav puan\u0131n\u0131n 48,56 oldu\u011fu anlam\u0131na gelir.<\/span><\/p>\n

      Kesi\u015fme i\u00e7in regresyon katsay\u0131s\u0131n\u0131n yaln\u0131zca modeldeki t\u00fcm yorday\u0131c\u0131 de\u011fi\u015fkenlerin asl\u0131nda s\u0131f\u0131ra e\u015fit olmas\u0131n\u0131n makul olmas\u0131 durumunda anlaml\u0131 oldu\u011funu belirtmek \u00f6nemlidir. Bu \u00f6rnekte, bir \u00f6\u011frencinin s\u0131f\u0131r saat \u00e7al\u0131\u015fm\u0131\u015f olmas\u0131 ( \u00c7al\u0131\u015f\u0131lan saat = 0)<\/em> ve ayn\u0131 zamanda \u00f6zel \u00f6\u011fretmen kullanmam\u0131\u015f olmas\u0131 ( \u00d6\u011fretmen = 0) kesinlikle m\u00fcmk\u00fcnd\u00fcr.<\/em><\/span> Dolay\u0131s\u0131yla bu \u00f6rnekte kesmenin regresyon katsay\u0131s\u0131n\u0131n yorumu anlaml\u0131d\u0131r.<\/span><\/p>\n

      Ancak baz\u0131 durumlarda kesmeye ili\u015fkin regresyon katsay\u0131s\u0131 anlaml\u0131 de\u011fildir. \u00d6rne\u011fin, tahmin de\u011fi\u015fkeni olarak metrekareyi<\/em> ve yan\u0131t de\u011fi\u015fkeni olarak ev de\u011ferini<\/em> kullanarak bir regresyon analizi yapt\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m.<\/span><\/p>\n

      \u00c7\u0131kt\u0131 regresyon tablosunda bir evin metrekaresi<\/em> hi\u00e7bir zaman s\u0131f\u0131ra e\u015fit olamayaca\u011f\u0131ndan orijinal terime ait regresyon katsay\u0131s\u0131n\u0131n anlaml\u0131 bir yorumu olmayacakt\u0131r. Bu durumda orijinal terimin regresyon katsay\u0131s\u0131, regresyon do\u011frusunu do\u011fru yere tutturur.<\/span><\/p>\n

      S\u00fcrekli bir yorday\u0131c\u0131 de\u011fi\u015fkenin katsay\u0131s\u0131n\u0131n yorumlanmas\u0131<\/strong><\/span><\/h2>\n

      S\u00fcrekli bir yorday\u0131c\u0131 de\u011fi\u015fken i\u00e7in regresyon katsay\u0131s\u0131, di\u011fer t\u00fcm yorday\u0131c\u0131 de\u011fi\u015fkenlerin sabit kald\u0131\u011f\u0131 varsay\u0131larak, yorday\u0131c\u0131 de\u011fi\u015fkendeki her bir birimlik de\u011fi\u015fiklik i\u00e7in yan\u0131t de\u011fi\u015fkeninin \u00f6ng\u00f6r\u00fclen de\u011feri aras\u0131ndaki fark\u0131 temsil eder.<\/span><\/p>\n

      Bu \u00f6rnekte \u00e7al\u0131\u015f\u0131lan saat<\/em> , 0 ila 20 saat aras\u0131nda de\u011fi\u015fen s\u00fcrekli bir \u00f6ng\u00f6r\u00fcc\u00fc de\u011fi\u015fkendir. Baz\u0131 durumlarda bir \u00f6\u011frenci yaln\u0131zca s\u0131f\u0131r saat \u00e7al\u0131\u015ft\u0131, di\u011fer durumlarda ise bir \u00f6\u011frenci 20 saate kadar \u00e7al\u0131\u015ft\u0131.<\/span><\/p>\n

      Regresyon sonucundan \u00e7al\u0131\u015f\u0131lan saatlere<\/em> ait regresyon katsay\u0131s\u0131n\u0131n 2,03<\/strong> oldu\u011funu g\u00f6r\u00fcyoruz. Bu, tahmin de\u011fi\u015fkeni Tutor’un<\/em> sabit tutuldu\u011fu varsay\u0131ld\u0131\u011f\u0131nda, \u00e7al\u0131\u015f\u0131lan her ek saatin final s\u0131nav\u0131nda ortalama 2,03 puanl\u0131k bir art\u0131\u015fla ili\u015fkili oldu\u011fu anlam\u0131na gelir.<\/span><\/p>\n

      \u00d6rne\u011fin, 10 saat ders \u00e7al\u0131\u015fan ve \u00f6zel \u00f6\u011fretmen kullanan A \u00f6\u011frencisini d\u00fc\u015f\u00fcn\u00fcn. Ayr\u0131ca 11 saat \u00e7al\u0131\u015fan ve ayn\u0131 zamanda \u00f6zel \u00f6\u011fretmen kullanan \u00d6\u011frenci B’yi de d\u00fc\u015f\u00fcn\u00fcn. Regresyon sonu\u00e7lar\u0131m\u0131za g\u00f6re \u00d6\u011frenci B’nin s\u0131navda \u00d6\u011frenci A’dan 2,03 puan daha y\u00fcksek almas\u0131 bekleniyor.<\/span><\/p>\n

      Regresyon tablosunun p de\u011feri bize bu regresyon katsay\u0131s\u0131n\u0131n ger\u00e7ekten istatistiksel olarak anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 s\u00f6yler. \u00c7al\u0131\u015f\u0131lan saatlere<\/em> ili\u015fkin p de\u011ferinin 0,009<\/strong> oldu\u011funu ve bunun 0,05 alfa d\u00fczeyinde istatistiksel olarak anlaml\u0131 oldu\u011funu g\u00f6r\u00fcyoruz.<\/span><\/p>\n

      Not:<\/strong> Regresyon analizini ger\u00e7ekle\u015ftirmeden \u00f6nce alfa d\u00fczeyi se\u00e7ilmelidir; alfa d\u00fczeyi i\u00e7in yayg\u0131n se\u00e7enekler 0,01, 0,05 ve 0,10’dur.<\/span><\/p>\n

      \u0130lgili makale:<\/strong> P de\u011ferlerinin a\u00e7\u0131klamas\u0131 ve istatistiksel \u00f6nemi<\/span><\/p>\n

      Kategorik bir yorday\u0131c\u0131 de\u011fi\u015fkenin katsay\u0131s\u0131n\u0131n yorumlanmas\u0131<\/strong><\/span><\/h2>\n

      Kategorik bir yorday\u0131c\u0131 de\u011fi\u015fken i\u00e7in regresyon katsay\u0131s\u0131, yorday\u0131c\u0131 de\u011fi\u015fkenin = 0 oldu\u011fu kategori ile yorday\u0131c\u0131 de\u011fi\u015fkenin = 1 oldu\u011fu kategori aras\u0131ndaki yan\u0131t de\u011fi\u015fkeninin \u00f6ng\u00f6r\u00fclen de\u011ferindeki fark\u0131 temsil eder.<\/span><\/p>\n

      Bu \u00f6rnekte Tutor<\/em> , iki farkl\u0131 de\u011fer alabilen kategorik bir tahmin de\u011fi\u015fkenidir:<\/span><\/p>\n

        \n
      • 1 = \u00f6\u011frenci s\u0131nava haz\u0131rlanmak i\u00e7in bir \u00f6\u011fretmen kulland\u0131<\/span><\/li>\n
      • 0 = \u00f6\u011frenci s\u0131nava haz\u0131rlanmak i\u00e7in bir \u00f6\u011fretmen kullanmad\u0131<\/span><\/li>\n<\/ul>\n

        Regresyon sonucunda Tutor<\/em> i\u00e7in regresyon katsay\u0131s\u0131n\u0131n 8,34<\/strong> oldu\u011funu g\u00f6r\u00fcyoruz. Bu, \u00e7al\u0131\u015f\u0131lan saat<\/em> tahmin de\u011fi\u015fkeninin sabit kald\u0131\u011f\u0131 varsay\u0131ld\u0131\u011f\u0131nda, \u00f6zel \u00f6\u011fretmen kullanan bir \u00f6\u011frencinin, \u00f6zel \u00f6\u011fretmen kullanmayan bir \u00f6\u011frenciden s\u0131navda ortalama 8,34 puan daha y\u00fcksek puan ald\u0131\u011f\u0131 anlam\u0131na gelir.<\/span><\/p>\n

        \u00d6rne\u011fin, 10 saat ders \u00e7al\u0131\u015fan ve \u00f6zel \u00f6\u011fretmen kullanan A \u00f6\u011frencisini d\u00fc\u015f\u00fcn\u00fcn. Ayr\u0131ca 10 saat \u00e7al\u0131\u015fan ve \u00f6zel \u00f6\u011fretmen kullanmayan \u00d6\u011frenci B’yi de d\u00fc\u015f\u00fcn\u00fcn. Regresyon sonu\u00e7lar\u0131m\u0131za g\u00f6re \u00d6\u011frenci A’n\u0131n \u00d6\u011frenci B’den 8,34 puan daha y\u00fcksek bir s\u0131nav puan\u0131 almas\u0131 bekleniyor.<\/span><\/p>\n

        Regresyon tablosunun p de\u011feri bize bu regresyon katsay\u0131s\u0131n\u0131n ger\u00e7ekten istatistiksel olarak anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 s\u00f6yler. Tutor<\/em> i\u00e7in p de\u011ferinin 0,138<\/strong> oldu\u011funu ve bunun 0,05 alfa d\u00fczeyinde istatistiksel olarak anlaml\u0131 olmad\u0131\u011f\u0131n\u0131 g\u00f6rebiliriz. Bu durum, \u00f6zel ders veren \u00f6\u011frencilerin s\u0131navda daha iyi performans g\u00f6sterse de bu fark\u0131n \u015fanstan kaynaklanabilece\u011fini g\u00f6steriyor.<\/span><\/p>\n

        T\u00fcm katsay\u0131lar\u0131 ayn\u0131 anda yorumlay\u0131n<\/strong><\/span><\/h2>\n

        A\u015fa\u011f\u0131daki tahmini regresyon denklemini olu\u015fturmak i\u00e7in regresyon tablosundaki t\u00fcm katsay\u0131lar\u0131 kullanabiliriz:<\/span><\/p>\n

        Beklenen s\u0131nav puan\u0131 = 48,56 + 2,03*(\u00c7al\u0131\u015f\u0131lan saat) + 8,34*(\u00d6\u011fretmen)<\/span><\/p>\n

        Not<\/strong> :<\/strong> “\u00d6\u011fretmen” yorday\u0131c\u0131 de\u011fi\u015fkeninin 0,05 alfa seviyesinde istatistiksel olarak anlaml\u0131 olmad\u0131\u011f\u0131n\u0131 unutmay\u0131n; dolay\u0131s\u0131yla bu yorday\u0131c\u0131y\u0131 modelden \u00e7\u0131karmay\u0131 ve onu regresyon denklemi nihai tahmininde kullanmamay\u0131 se\u00e7ebilirsiniz.<\/em><\/span><\/p>\n

        Bu tahmini regresyon denklemini kullanarak, bir \u00f6\u011frencinin final s\u0131nav\u0131 notunu toplam \u00e7al\u0131\u015fma saatine ve \u00f6zel ders al\u0131p almad\u0131\u011f\u0131na g\u00f6re tahmin edebiliriz.<\/span><\/p>\n

        \u00d6rne\u011fin, 10 saat \u00e7al\u0131\u015f\u0131p \u00f6zel ders veren bir \u00f6\u011frencinin s\u0131nav puan\u0131 \u015fu \u015fekilde olmal\u0131d\u0131r:<\/span><\/p>\n

        Beklenen s\u0131nav puan\u0131 = 48,56 + 2,03*(10) + 8,34*(1) = 77,2<\/strong><\/span><\/p>\n

        Regresyon katsay\u0131lar\u0131n\u0131 yorumlarken korelasyonun dikkate al\u0131nmas\u0131<\/strong><\/span><\/h2>\n

        Bir regresyon modelinde yorday\u0131c\u0131 de\u011fi\u015fkenlerin birbirini etkileyebilece\u011fini ak\u0131lda tutmak \u00f6nemlidir. \u00d6rne\u011fin, yorday\u0131c\u0131 de\u011fi\u015fkenlerin \u00e7o\u011fu en az\u0131ndan bir \u015fekilde birbiriyle ili\u015fkili olacakt\u0131r (\u00f6rne\u011fin, daha fazla \u00e7al\u0131\u015fan bir \u00f6\u011frencinin \u00f6zel ders verme olas\u0131l\u0131\u011f\u0131 da daha y\u00fcksektir).<\/span><\/p>\n

        Bu, farkl\u0131 yorday\u0131c\u0131 de\u011fi\u015fkenler modele eklendi\u011finde veya modelden \u00e7\u0131kar\u0131ld\u0131\u011f\u0131nda regresyon katsay\u0131lar\u0131n\u0131n de\u011fi\u015fece\u011fi anlam\u0131na gelir.<\/span><\/p>\n

        Yorday\u0131c\u0131 de\u011fi\u015fkenler aras\u0131ndaki korelasyonun, regresyon modelini ciddi \u015fekilde etkileyecek kadar ciddi olup olmad\u0131\u011f\u0131n\u0131 g\u00f6rmenin iyi bir yolu , yorday\u0131c\u0131 de\u011fi\u015fkenler aras\u0131ndaki VIF’yi kontrol etmektir .<\/span><\/p>\n

        Bu size, yorday\u0131c\u0131 de\u011fi\u015fkenler aras\u0131ndaki korelasyonun, regresyon katsay\u0131lar\u0131n\u0131 yorumlamaya karar vermeden \u00f6nce \u00e7\u00f6z\u00fclmesi gereken bir sorun olup olmad\u0131\u011f\u0131n\u0131 s\u00f6yleyecektir.<\/span><\/p>\n

        Tek bir \u00f6ng\u00f6r\u00fcc\u00fcyle basit bir do\u011frusal regresyon modeli \u00e7al\u0131\u015ft\u0131r\u0131rsan\u0131z, ili\u015fkili yorday\u0131c\u0131 de\u011fi\u015fkenler sorun olmayacakt\u0131r.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

        \u0130statistikteregresyon analizi , yorday\u0131c\u0131 de\u011fi\u015fkenler ile bir yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fkiyi analiz etmek i\u00e7in kullan\u0131labilecek bir tekniktir. Regresyon analizini ger\u00e7ekle\u015ftirmek i\u00e7in yaz\u0131l\u0131m ( R , Stata , SPSS vb.) kulland\u0131\u011f\u0131n\u0131zda, regresyon sonu\u00e7lar\u0131n\u0131 \u00f6zetleyen bir regresyon tablosunu \u00e7\u0131kt\u0131 olarak alacaks\u0131n\u0131z. Regresyon tablosu sonucundaki en \u00f6nemli say\u0131lar muhtemelen regresyon katsay\u0131lar\u0131d\u0131r . Ancak \u00f6nemlerine ra\u011fmen bir\u00e7ok ki\u015fi bu […]<\/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-543","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nRegresyon katsay\u0131lar\u0131 nas\u0131l yorumlan\u0131r - Statorials<\/title>\n<meta name=\"description\" content=\"Regresyon analizinde regresyon katsay\u0131lar\u0131n\u0131n nas\u0131l yorumlanaca\u011f\u0131na dair basit bir a\u00e7\u0131klama.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Regresyon katsay\u0131lar\u0131 nas\u0131l yorumlan\u0131r - Statorials\" \/>\n<meta property=\"og:description\" content=\"Regresyon analizinde regresyon katsay\u0131lar\u0131n\u0131n nas\u0131l yorumlanaca\u011f\u0131na dair basit bir a\u00e7\u0131klama.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-29T13:49:52+00:00\" \/>\n<meta name=\"author\" content=\"Dr.benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Dr.benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/\",\"url\":\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/\",\"name\":\"Regresyon katsay\u0131lar\u0131 nas\u0131l yorumlan\u0131r - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/tr\/#website\"},\"datePublished\":\"2023-07-29T13:49:52+00:00\",\"dateModified\":\"2023-07-29T13:49:52+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\"},\"description\":\"Regresyon analizinde regresyon katsay\u0131lar\u0131n\u0131n nas\u0131l yorumlanaca\u011f\u0131na dair basit bir a\u00e7\u0131klama.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/tr\/regresyon-katsayilari-nasil-yorumlanir\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Ev\",\"item\":\"https:\/\/statorials.org\/tr\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Regresyon katsay\u0131lar\u0131 nas\u0131l yorumlan\u0131r?\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/tr\/#website\",\"url\":\"https:\/\/statorials.org\/tr\/\",\"name\":\"Statorials\",\"description\":\"\u0130statistik okuryazarl\u0131\u011f\u0131 rehberiniz!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/tr\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"tr\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\",\"name\":\"Dr.benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"tr\",\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Dr.benjamin anderson\"},\"description\":\"Merhaba, ben Benjamin, emekli bir istatistik profes\u00f6r\u00fc ve Statorials \u00f6\u011fretmenine d\u00f6n\u00fc\u015ft\u00fcm. \u0130statistik alan\u0131ndaki kapsaml\u0131 deneyimim ve uzmanl\u0131\u011f\u0131mla, \u00f6\u011frencilerimi Statorials arac\u0131l\u0131\u011f\u0131yla g\u00fc\u00e7lendirmek i\u00e7in bilgilerimi payla\u015fmaya can at\u0131yorum. 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