{"id":310,"date":"2023-08-02T17:51:20","date_gmt":"2023-08-02T17:51:20","guid":{"rendered":"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/"},"modified":"2023-08-02T17:51:20","modified_gmt":"2023-08-02T17:51:20","slug":"lojistik-regresyon-1","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/","title":{"rendered":"Lojistik regresyon"},"content":{"rendered":"

Bu makale istatistikte lojistik regresyonun ne oldu\u011funu a\u00e7\u0131klamaktad\u0131r. Benzer \u015fekilde, lojistik regresyon form\u00fcl\u00fcn\u00fc, farkl\u0131 lojistik regresyon t\u00fcrlerinin neler oldu\u011funu ve ayr\u0131ca \u00e7\u00f6z\u00fclm\u00fc\u015f bir lojistik regresyon al\u0131\u015ft\u0131rmas\u0131n\u0131 bulacaks\u0131n\u0131z. <\/p>\n

<\/span> Lojistik regresyon nedir?<\/span><\/h2>\n

\u0130statistikte lojistik regresyon<\/strong> , kategorik bir de\u011fi\u015fkenin<\/a> sonucunu tahmin etmek i\u00e7in kullan\u0131lan bir t\u00fcr regresyon modelidir. Yani, kategorik bir de\u011fi\u015fkenin ba\u011f\u0131ms\u0131z de\u011fi\u015fkenlere g\u00f6re belirli bir de\u011fer alma olas\u0131l\u0131\u011f\u0131n\u0131 modellemek i\u00e7in lojistik regresyon kullan\u0131l\u0131r.<\/p>\n

En yayg\u0131n lojistik regresyon modeli, yaln\u0131zca iki olas\u0131 sonucun oldu\u011fu ikili lojistik regresyondur: “ba\u015far\u0131s\u0131zl\u0131k” veya “ba\u015far\u0131” ( Bernoulli da\u011f\u0131l\u0131m\u0131<\/a> ). \u201cBa\u015far\u0131s\u0131zl\u0131k\u201d 0 de\u011feriyle, \u201cba\u015far\u0131\u201d ise 1 de\u011feriyle temsil edilir.<\/p>\n

\u00d6rne\u011fin bir \u00f6\u011frencinin ders \u00e7al\u0131\u015farak ge\u00e7irdi\u011fi saatlere g\u00f6re s\u0131nav\u0131 ge\u00e7me olas\u0131l\u0131\u011f\u0131 lojistik regresyon modeli kullan\u0131larak incelenebilir. Bu durumda ba\u015far\u0131s\u0131zl\u0131k \u201cba\u015far\u0131s\u0131zl\u0131\u011f\u0131n\u201d sonucu, ba\u015far\u0131 ise \u201cba\u015far\u0131\u201dn\u0131n sonucu olacakt\u0131r. <\/p>\n

<\/span> Lojistik Regresyon Form\u00fcl\u00fc<\/span><\/h2>\n

Lojistik regresyon modelinin denklemi \u015f\u00f6yledir:<\/p>\n<\/p>\n

\"\\displaystyle<\/p>\n<\/p>\n

Dolay\u0131s\u0131yla lojistik regresyon modelinde \u201cba\u015far\u0131l\u0131\u201d sonucunun yani ba\u011f\u0131ml\u0131 de\u011fi\u015fkenin 1 de\u011ferini almas\u0131 olas\u0131l\u0131\u011f\u0131 a\u015fa\u011f\u0131daki form\u00fclle hesaplan\u0131r:<\/p>\n<\/p>\n

\"p=\\cfrac{1}{1+e^{-(\\beta_0+\\beta_1x_1+\\beta_2x_2+\\dots+\\beta_ix_i)}}\"<\/p>\n<\/p>\n

Alt\u0131n:<\/p>\n

    \n
  • \n

    \"p\"<\/p>\n

    ba\u011f\u0131ml\u0131 de\u011fi\u015fkenin 1 olma olas\u0131l\u0131\u011f\u0131d\u0131r.<\/li>\n

  • \n

    \"\\beta_0\"<\/p>\n

    lojistik regresyon modelinin sabitidir.<\/li>\n

  • \n

    \"\\beta_i\"<\/p>\n

    i de\u011fi\u015fkeninin regresyon katsay\u0131s\u0131d\u0131r.<\/li>\n

  • \n

    \"x_i\"<\/p>\n

    i de\u011fi\u015fkeninin de\u011feridir. <\/li>\n<\/ul>\n

    <\/span> Lojistik Regresyon Modeli \u00d6rne\u011fi<\/span><\/h2>\n

    Art\u0131k lojistik regresyonun tan\u0131m\u0131n\u0131 bildi\u011fimize g\u00f6re, bu t\u00fcr bir regresyon modelinin nas\u0131l olu\u015fturulaca\u011f\u0131na dair somut bir \u00f6rnek g\u00f6relim.<\/p>\n

      \n
    • A\u015fa\u011f\u0131daki tabloda, her \u00f6\u011frencinin \u00e7al\u0131\u015fma saatleri ve bir istatistik s\u0131nav\u0131n\u0131 ge\u00e7ip ge\u00e7medi\u011fi ile ilgili 20 par\u00e7al\u0131k bir veri dizisi derlenmi\u015ftir. Lojistik regresyon modelini \u00e7al\u0131\u015ft\u0131r\u0131n ve bir \u00f6\u011frencinin 4 saat \u00e7al\u0131\u015fmas\u0131 durumunda ba\u015far\u0131l\u0131 olma olas\u0131l\u0131\u011f\u0131n\u0131 hesaplay\u0131n. <\/li>\n<\/ul>\n
      \"\"<\/figure>\n

      Bu durumda a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fken, \u00e7al\u0131\u015fma saati say\u0131s\u0131d\u0131r ve yan\u0131t de\u011fi\u015fkeni, \u00f6\u011frencinin ba\u015far\u0131s\u0131z olup olmad\u0131\u011f\u0131 (0) veya ba\u015far\u0131l\u0131 olup olmad\u0131\u011f\u0131d\u0131r (1). Bu nedenle modelimizde sadece katsay\u0131ya sahip olaca\u011f\u0131z.<\/p>\n<\/p>\n

      \"\\beta_0\"<\/p>\n

      ve katsay\u0131<\/p>\n

      \"\\beta_1\"<\/p>\n

      \u00c7\u00fcnk\u00fc tek bir ba\u011f\u0131ms\u0131z de\u011fi\u015fken vard\u0131r.<\/p>\n<\/p>\n

      \"\\beta_0<\/p>\n<\/p>\n

      Regresyon katsay\u0131lar\u0131n\u0131n manuel olarak belirlenmesi olduk\u00e7a zahmetli oldu\u011fundan Minitab gibi bilgisayar yaz\u0131l\u0131mlar\u0131n\u0131n kullan\u0131lmas\u0131 tavsiye edilir. B\u00f6ylece Minitab kullan\u0131larak hesaplanan regresyon katsay\u0131lar\u0131n\u0131n de\u011ferleri a\u015fa\u011f\u0131daki gibidir:<\/p>\n<\/p>\n

      \"\\begin{array}{c}\\beta_0\\approx<\/p>\n<\/p>\n

      Dolay\u0131s\u0131yla lojistik regresyon modeli a\u015fa\u011f\u0131daki gibidir:<\/p>\n<\/p>\n

      \"\\begin{aligned}p&=\\cfrac{1}{1+e^{-(\\beta_0+\\beta_1x_1+\\beta_2x_2+\\dots+\\beta_ix_i)}}\\\\[2ex]p&=\\cfrac{1}{1+e^{-(-4,1+1,5x_1)}}\\\\[2ex]p&=\\cfrac{1}{1+e^{4,1-1,5x_1}}\\end{aligned}\"<\/p>\n<\/p>\n

      A\u015fa\u011f\u0131da \u00f6rnek verileri ve lojistik regresyon modeli denkleminin grafi\u011fini g\u00f6rebilirsiniz: <\/p>\n

      \"lojistik<\/figure>\n

      Bu nedenle, bir \u00f6\u011frencinin 4 saat \u00e7al\u0131\u015fmas\u0131 durumunda ba\u015far\u0131l\u0131 olma olas\u0131l\u0131\u011f\u0131n\u0131 hesaplamak i\u00e7in lojistik regresyon modelinden elde edilen denklemi kullanman\u0131z yeterlidir:<\/p>\n<\/p>\n

      \"\\begin{aligned}p&=\\cfrac{1}{1+e^{4,1-1,5x_1}}\\\\[2ex]p&=\\cfrac{1}{1+e^{4,1-1,5\\cdot<\/p>\n<\/p>\n

      K\u0131saca bir \u00f6\u011frenci d\u00f6rt saat ders \u00e7al\u0131\u015f\u0131rsa s\u0131nav\u0131 ge\u00e7me ihtimali %86,99 olacakt\u0131r. <\/p>\n

      <\/span> Lojistik Regresyon T\u00fcrleri<\/span><\/h2>\n

      \u00dc\u00e7 t\u00fcr lojistik regresyon<\/strong> vard\u0131r:<\/p>\n

        \n
      • \u0130kili Lojistik Regresyon<\/strong> : Ba\u011f\u0131ml\u0131 de\u011fi\u015fken yaln\u0131zca iki de\u011fere (0 ve 1) sahip olabilir.<\/span><\/li>\n
      • \u00c7ok terimli lojistik regresyon<\/strong> : Ba\u011f\u0131ml\u0131 de\u011fi\u015fkenin ikiden fazla olas\u0131 de\u011feri vard\u0131r.<\/span><\/li>\n
      • S\u0131ral\u0131 lojistik regresyon<\/strong> : olas\u0131 sonu\u00e7lar\u0131n do\u011fal bir s\u0131ras\u0131 vard\u0131r.<\/span> <\/li>\n<\/ul>\n

        <\/span> Lojistik regresyon ve do\u011frusal regresyon<\/span><\/h2>\n

        Son olarak \u00f6zetle lojistik regresyon ile do\u011frusal regresyon aras\u0131ndaki fark\u0131n ne oldu\u011funu g\u00f6rece\u011fiz, \u00e7\u00fcnk\u00fc istatistikte en \u00e7ok kullan\u0131lan regresyon modeli do\u011frusal modeldir.<\/p>\n

        Say\u0131sal ba\u011f\u0131ml\u0131 de\u011fi\u015fkenleri modellemek i\u00e7in do\u011frusal regresyon<\/strong> kullan\u0131l\u0131r. Ek olarak do\u011frusal regresyonda a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fkenler ile yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fki do\u011frusald\u0131r.<\/p>\n

        Bu nedenle lojistik regresyon ile do\u011frusal regresyon aras\u0131ndaki temel fark<\/strong> ba\u011f\u0131ml\u0131 de\u011fi\u015fkenin t\u00fcr\u00fcd\u00fcr. Lojistik regresyonda ba\u011f\u0131ml\u0131 de\u011fi\u015fken kategoriktir, do\u011frusal regresyonda ise ba\u011f\u0131ml\u0131 de\u011fi\u015fken say\u0131sald\u0131r.<\/p>\n

        Bu nedenle, lojistik regresyon iki olas\u0131 se\u00e7enek aras\u0131ndaki sonucu tahmin etmek i\u00e7in kullan\u0131l\u0131rken, do\u011frusal regresyon say\u0131sal bir sonucu tahmin etmeye yard\u0131mc\u0131 olur.<\/p>\n","protected":false},"excerpt":{"rendered":"

        Bu makale istatistikte lojistik regresyonun ne oldu\u011funu a\u00e7\u0131klamaktad\u0131r. Benzer \u015fekilde, lojistik regresyon form\u00fcl\u00fcn\u00fc, farkl\u0131 lojistik regresyon t\u00fcrlerinin neler oldu\u011funu ve ayr\u0131ca \u00e7\u00f6z\u00fclm\u00fc\u015f bir lojistik regresyon al\u0131\u015ft\u0131rmas\u0131n\u0131 bulacaks\u0131n\u0131z. Lojistik regresyon nedir? \u0130statistikte lojistik regresyon , kategorik bir de\u011fi\u015fkenin sonucunu tahmin etmek i\u00e7in kullan\u0131lan bir t\u00fcr regresyon modelidir. Yani, kategorik bir de\u011fi\u015fkenin ba\u011f\u0131ms\u0131z de\u011fi\u015fkenlere g\u00f6re belirli bir […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14],"tags":[],"class_list":["post-310","post","type-post","status-publish","format-standard","hentry","category-istatistik"],"yoast_head":"\n\u25b7 Lojistik regresyon<\/title>\n<meta name=\"description\" content=\"Burada lojistik regresyonun ne oldu\u011funu, form\u00fcllerini, somut bir \u00f6rne\u011fini ve farkl\u0131 lojistik regresyon t\u00fcrlerinin neler oldu\u011funu ke\u015ffedeceksiniz.\" \/>\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\/lojistik-regresyon-1\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u25b7 Lojistik regresyon\" \/>\n<meta property=\"og:description\" content=\"Burada lojistik regresyonun ne oldu\u011funu, form\u00fcllerini, somut bir \u00f6rne\u011fini ve farkl\u0131 lojistik regresyon t\u00fcrlerinin neler oldu\u011funu ke\u015ffedeceksiniz.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-08-02T17:51:20+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/ql-cache\/quicklatex.com-dc942e1e0ee36da34fb21da18308159b_l3.png\" \/>\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=\"4 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/\",\"url\":\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/\",\"name\":\"\u25b7 Lojistik regresyon\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/tr\/#website\"},\"datePublished\":\"2023-08-02T17:51:20+00:00\",\"dateModified\":\"2023-08-02T17:51:20+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\"},\"description\":\"Burada lojistik regresyonun ne oldu\u011funu, form\u00fcllerini, somut bir \u00f6rne\u011fini ve farkl\u0131 lojistik regresyon t\u00fcrlerinin neler oldu\u011funu ke\u015ffedeceksiniz.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/tr\/lojistik-regresyon-1\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Ev\",\"item\":\"https:\/\/statorials.org\/tr\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Lojistik regresyon\"}]},{\"@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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