{"id":629,"date":"2023-07-29T06:59:56","date_gmt":"2023-07-29T06:59:56","guid":{"rendered":"https:\/\/statorials.org\/tr\/saglam-standart-hata-istatistikleri\/"},"modified":"2023-07-29T06:59:56","modified_gmt":"2023-07-29T06:59:56","slug":"saglam-standart-hata-istatistikleri","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/saglam-standart-hata-istatistikleri\/","title":{"rendered":"Stata'da regresyonda sa\u011flam standart hatalar nas\u0131l kullan\u0131l\u0131r?"},"content":{"rendered":"

<\/p>\n

\n

\u00c7oklu do\u011frusal regresyon,<\/a> birden fazla a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fken ile bir yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fkiyi anlamak i\u00e7in kullanabilece\u011fimiz bir y\u00f6ntemdir.<\/span><\/p>\n

Ne yaz\u0131k ki, regresyonda s\u0131kl\u0131kla ortaya \u00e7\u0131kan bir sorun, \u00f6l\u00e7\u00fclen de\u011ferler aral\u0131\u011f\u0131 boyunca art\u0131klar\u0131n varyans\u0131nda sistematik bir de\u011fi\u015fikli\u011fin oldu\u011fu, de\u011fi\u015fen varyans<\/a> olarak bilinir.<\/span><\/p>\n

Bu durum regresyon katsay\u0131s\u0131 tahminlerinin varyans\u0131n\u0131n artmas\u0131na neden olur ancak regresyon modeli bunu dikkate almaz. Bu, ger\u00e7ekte \u00f6yle olmad\u0131\u011f\u0131 halde, bir regresyon modelinin, modeldeki bir terimin istatistiksel olarak anlaml\u0131 oldu\u011funu iddia etme olas\u0131l\u0131\u011f\u0131n\u0131 \u00e7ok daha art\u0131r\u0131r.<\/span><\/p>\n

Bu sorunu a\u00e7\u0131klaman\u0131n bir yolu, heteroskedastisite sorununa kar\u015f\u0131 daha “sa\u011flam” olan ve bir regresyon katsay\u0131s\u0131n\u0131n ger\u00e7ek standart hatas\u0131n\u0131n daha do\u011fru bir \u00f6l\u00e7\u00fcm\u00fcn\u00fc sa\u011flama e\u011filiminde olan sa\u011flam standart hatalar\u0131n<\/strong> kullan\u0131lmas\u0131d\u0131r.<\/span><\/p>\n

Bu e\u011fitimde Stata’da regresyon analizinde sa\u011flam standart hatalar\u0131n nas\u0131l kullan\u0131laca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n

\u00d6rnek: Stata’daki sa\u011flam standart hatalar<\/strong><\/span><\/h2>\n

Regresyonda sa\u011flam standart hatalar\u0131n nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermek i\u00e7in otomatik olarak<\/em> entegre edilen Stata veri k\u00fcmesini kullanaca\u011f\u0131z.<\/span><\/p>\n

Ad\u0131m 1: Verileri y\u00fckleyin ve g\u00f6r\u00fcnt\u00fcleyin.<\/strong><\/span><\/p>\n

\u00d6ncelikle verileri y\u00fcklemek i\u00e7in a\u015fa\u011f\u0131daki komutu kullan\u0131n:<\/span><\/p>\n

\n

sistemin otomatik kullan\u0131m\u0131<\/span><\/strong><\/p>\n<\/blockquote>\n

Daha sonra a\u015fa\u011f\u0131daki komutu kullanarak ham verileri g\u00f6r\u00fcnt\u00fcleyin:<\/span><\/p>\n

\n

br<\/strong><\/span> <\/p>\n<\/blockquote>\n

\"Stata'da<\/p>\n

Ad\u0131m 2: Sa\u011flam standart hatalar olmadan \u00e7oklu do\u011frusal regresyon ger\u00e7ekle\u015ftirin.<\/strong><\/span><\/p>\n

Daha sonra, yan\u0131t de\u011fi\u015fkeni olarak fiyat\u0131<\/em> ve a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fkenler olarak mpg<\/em> ve a\u011f\u0131rl\u0131\u011f\u0131<\/em> kullanarak \u00e7oklu do\u011frusal regresyon ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki komutu girece\u011fiz:<\/span><\/p>\n

\n

regresyon fiyat\u0131 mpg a\u011f\u0131rl\u0131\u011f\u0131<\/strong><\/span> <\/p>\n<\/blockquote>\n

\"Stata'da<\/p>\n

Ad\u0131m 3: Sa\u011flam standart hatalar\u0131 kullanarak \u00e7oklu do\u011frusal regresyon ger\u00e7ekle\u015ftirin.<\/strong><\/span><\/p>\n

\u015eimdi tam olarak ayn\u0131 \u00e7oklu do\u011frusal regresyonu ger\u00e7ekle\u015ftirece\u011fiz, ancak bu sefer vce(robust)<\/strong> komutunu kullanaca\u011f\u0131z, b\u00f6ylece Stata sa\u011flam standart hatalar\u0131n nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 bilir:<\/span><\/p>\n

\n

regresyon fiyat\u0131 mpg a\u011f\u0131rl\u0131\u011f\u0131, vce (sa\u011flam)<\/strong><\/span> <\/p>\n<\/blockquote>\n

\"Stata'da<\/p>\n

Burada dikkat edilmesi gereken birka\u00e7 ilgin\u00e7 nokta var:<\/span><\/p>\n

1. Katsay\u0131 tahminleri ayn\u0131 kald\u0131<\/strong> . Sa\u011flam standart hatalar kulland\u0131\u011f\u0131m\u0131zda katsay\u0131 tahminleri hi\u00e7 de\u011fi\u015fmez. Mpg, a\u011f\u0131rl\u0131k ve sabit i\u00e7in katsay\u0131 tahminlerinin her iki regresyon i\u00e7in de a\u015fa\u011f\u0131daki gibi oldu\u011funa dikkat edin:<\/span><\/p>\n

    \n
  • mpg:<\/strong> -49.51222<\/span><\/li>\n
  • a\u011f\u0131rl\u0131k:<\/strong> 1,746559<\/span><\/li>\n
  • _kar\u015f\u0131:<\/strong> 1946.069<\/span><\/li>\n<\/ul>\n

    2. Standart hatalar de\u011fi\u015fti<\/strong> . Sa\u011flam standart hatalar kulland\u0131\u011f\u0131m\u0131zda, katsay\u0131 tahminlerinin her biri i\u00e7in standart hatalar\u0131n artt\u0131\u011f\u0131n\u0131 unutmay\u0131n.<\/span><\/p>\n

    Not:<\/strong> \u00c7o\u011fu durumda sa\u011flam standart hatalar normal standart hatalardan daha b\u00fcy\u00fck olacakt\u0131r, ancak nadir durumlarda sa\u011flam standart hatalar\u0131n ger\u00e7ekte daha k\u00fc\u00e7\u00fck olmas\u0131 m\u00fcmk\u00fcnd\u00fcr.<\/em><\/span><\/p>\n

    3. Her katsay\u0131n\u0131n test istatisti\u011fi de\u011fi\u015fti.<\/strong> Her test istatisti\u011finin mutlak de\u011feri olan t’nin<\/em> azald\u0131\u011f\u0131na dikkat edin. Asl\u0131nda test istatisti\u011fi, tahmin edilen katsay\u0131n\u0131n standart hataya b\u00f6l\u00fcnmesiyle hesaplan\u0131r. Dolay\u0131s\u0131yla standart hata ne kadar b\u00fcy\u00fck olursa, test istatisti\u011finin mutlak de\u011feri de o kadar k\u00fc\u00e7\u00fck olur.<\/span><\/p>\n

    4. P de\u011ferleri de\u011fi\u015fti<\/strong> . Her de\u011fi\u015fkenin p de\u011ferlerinin de artt\u0131\u011f\u0131n\u0131 unutmay\u0131n. Bunun nedeni, daha k\u00fc\u00e7\u00fck test istatistiklerinin daha b\u00fcy\u00fck p de\u011ferleri ile ili\u015fkili olmas\u0131d\u0131r.<\/span><\/p>\n

    Katsay\u0131lar\u0131m\u0131z i\u00e7in p de\u011ferleri de\u011fi\u015fmi\u015f olsa da mpg<\/em> de\u011fi\u015fkeni \u03b1 = 0,05’te hala istatistiksel olarak anlaml\u0131 de\u011fildir ve de\u011fi\u015fken a\u011f\u0131rl\u0131\u011f\u0131<\/em> \u03b1 = 0,05’te hala istatistiksel olarak anlaml\u0131d\u0131r.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

    \u00c7oklu do\u011frusal regresyon, birden fazla a\u00e7\u0131klay\u0131c\u0131 de\u011fi\u015fken ile bir yan\u0131t de\u011fi\u015fkeni aras\u0131ndaki ili\u015fkiyi anlamak i\u00e7in kullanabilece\u011fimiz bir y\u00f6ntemdir. Ne yaz\u0131k ki, regresyonda s\u0131kl\u0131kla ortaya \u00e7\u0131kan bir sorun, \u00f6l\u00e7\u00fclen de\u011ferler aral\u0131\u011f\u0131 boyunca art\u0131klar\u0131n varyans\u0131nda sistematik bir de\u011fi\u015fikli\u011fin oldu\u011fu, de\u011fi\u015fen varyans olarak bilinir. Bu durum regresyon katsay\u0131s\u0131 tahminlerinin varyans\u0131n\u0131n artmas\u0131na neden olur ancak regresyon modeli bunu dikkate […]<\/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-629","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nStata'da regresyonda sa\u011flam standart hatalar nas\u0131l kullan\u0131l\u0131r - Statorials<\/title>\n<meta name=\"description\" content=\"Stata'da regresyon analizinde sa\u011flam standart hatalar\u0131n nas\u0131l kullan\u0131laca\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\/saglam-standart-hata-istatistikleri\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Stata'da regresyonda sa\u011flam standart hatalar nas\u0131l kullan\u0131l\u0131r - 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