{"id":418,"date":"2023-07-30T05:00:57","date_gmt":"2023-07-30T05:00:57","guid":{"rendered":"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/"},"modified":"2023-07-30T05:00:57","modified_gmt":"2023-07-30T05:00:57","slug":"dogrusal-regresyon","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/","title":{"rendered":"Basit do\u011frusal regresyona giri\u015f"},"content":{"rendered":"

<\/p>\n

\n

Basit do\u011frusal regresyon,<\/strong> iki de\u011fi\u015fken (x ve y) aras\u0131ndaki ili\u015fkiyi anlamak i\u00e7in kullanabilece\u011finiz istatistiksel bir y\u00f6ntemdir.<\/span><\/p>\n

Bir de\u011fi\u015fken olan x<\/strong> , yorday\u0131c\u0131 de\u011fi\u015fken<\/strong> olarak bilinir.<\/span><\/p>\n

Di\u011fer de\u011fi\u015fken, y<\/strong> , yan\u0131t de\u011fi\u015fkeni<\/strong> olarak bilinir.<\/span><\/p>\n

\u00d6rne\u011fin, yedi ki\u015finin a\u011f\u0131rl\u0131\u011f\u0131n\u0131 ve boyunu i\u00e7eren a\u015fa\u011f\u0131daki veri setine sahip oldu\u011fumuzu varsayal\u0131m:<\/span> <\/p>\n

\"Basit<\/p>\n

A\u011f\u0131rl\u0131k<\/em> belirleyici de\u011fi\u015fken olsun ve boy da<\/em> yan\u0131t de\u011fi\u015fkeni olsun.<\/span><\/p>\n

Bu iki de\u011fi\u015fkeni, x ekseninde a\u011f\u0131rl\u0131k ve y ekseninde y\u00fckseklik olacak \u015fekilde bir da\u011f\u0131l\u0131m grafi\u011fi kullanarak grafiklendirirsek, \u015f\u00f6yle g\u00f6r\u00fcnecektir:<\/span> <\/p>\n

\"Do\u011frusal<\/p>\n

A\u011f\u0131rl\u0131k ve boy aras\u0131ndaki ili\u015fkiyi anlamak istedi\u011fimizi varsayal\u0131m. Da\u011f\u0131l\u0131m grafi\u011finden, a\u011f\u0131rl\u0131k artt\u0131k\u00e7a boyun da artma e\u011filiminde oldu\u011funu a\u00e7\u0131k\u00e7a g\u00f6rebiliriz, ancak a\u011f\u0131rl\u0131k ile boy aras\u0131ndaki bu ili\u015fkiyi ger\u00e7ekte \u00f6l\u00e7mek<\/em> i\u00e7in do\u011frusal regresyon kullanmam\u0131z gerekir.<\/span><\/p>\n

Do\u011frusal regresyon kullanarak verilerimize en iyi “uyan” \u00e7izgiyi bulabiliriz. Bu \u00e7izgi en k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisi<\/strong> olarak bilinir ve a\u011f\u0131rl\u0131k ile boy aras\u0131ndaki ili\u015fkileri anlamam\u0131za yard\u0131mc\u0131 olmak i\u00e7in kullan\u0131labilir.<\/span><\/p>\n

Genellikle bu do\u011frunun denklemini bulmak i\u00e7in Microsoft Excel, SPSS gibi yaz\u0131l\u0131mlar\u0131 veya grafik hesap makinesini kullan\u0131rs\u0131n\u0131z.<\/span><\/p>\n

En iyi uyum \u00e7izgisinin form\u00fcl\u00fc yaz\u0131lm\u0131\u015ft\u0131r:<\/span><\/p>\n

\u0177 = b 0<\/sub> + b 1<\/sub> x<\/span><\/p>\n

burada \u0177 yan\u0131t de\u011fi\u015fkeninin tahmin edilen de\u011feridir, b 0<\/sub> kesi\u015fme noktas\u0131d\u0131r, b 1<\/sub> regresyon katsay\u0131s\u0131d\u0131r ve x yorday\u0131c\u0131 de\u011fi\u015fkenin de\u011feridir.<\/span><\/p>\n

\u0130lgili:<\/strong> Ger\u00e7ek Hayatta Do\u011frusal Regresyonun Kullan\u0131m\u0131na \u0130li\u015fkin 4 \u00d6rnek<\/a><\/span><\/p>\n

\u201cEn uygun seriyi\u201d bulun<\/span><\/strong><\/h2>\n

Bu \u00f6rnek i\u00e7in, verilerimizi istatistiksel do\u011frusal regresyon hesaplay\u0131c\u0131s\u0131na<\/a> ba\u011flay\u0131p Hesapla<\/em> tu\u015funa basabiliriz:<\/span> <\/p>\n

\"Do\u011frusal<\/p>\n

Hesap makinesi en k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisini<\/strong> otomatik olarak bulur:<\/span><\/p>\n

\u0177 = 32,7830 + 0,2001x<\/span><\/p>\n

\u00d6nceki da\u011f\u0131l\u0131m grafi\u011fimizden uzakla\u015f\u0131p bu \u00e7izgiyi grafi\u011fe eklersek, \u015f\u00f6yle g\u00f6r\u00fcnecektir:<\/span> <\/p>\n

\"\"<\/p>\n

Veri noktalar\u0131m\u0131z\u0131n bu \u00e7izgi etraf\u0131nda nas\u0131l da yak\u0131n bir \u015fekilde da\u011f\u0131ld\u0131\u011f\u0131na dikkat edin. Asl\u0131nda bu en k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisi, \u00e7izebilece\u011fimiz t\u00fcm olas\u0131 \u00e7izgiler aras\u0131nda verilerimize en uygun olan\u0131d\u0131r.<\/span><\/p>\n

En k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisi nas\u0131l yorumlan\u0131r<\/span><\/strong><\/h2>\n

Bu en k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisini \u015fu \u015fekilde yorumlayabilirsiniz: \u0177 = 32,7830 + 0,2001x<\/span><\/p>\n

b0<\/sub> = 32,7830<\/strong> . Bu, tahmin de\u011fi\u015fken a\u011f\u0131rl\u0131\u011f\u0131<\/em> s\u0131f\u0131r pound oldu\u011funda tahmin edilen y\u00fcksekli\u011fin 32,7830 in\u00e7 oldu\u011fu anlam\u0131na gelir. Bazen b 0’\u0131n<\/sub> de\u011ferini bilmek yararl\u0131 olabilir, ancak bu \u00f6zel \u00f6rnekte bir ki\u015fi s\u0131f\u0131r pound a\u011f\u0131rl\u0131\u011f\u0131nda olamayaca\u011f\u0131ndan b 0’\u0131<\/sub> yorumlaman\u0131n bir anlam\u0131 yoktur.<\/span><\/p>\n

b1<\/sub> = 0,2001<\/strong> . Bu, x’teki<\/em> bir birimlik art\u0131\u015f\u0131n, y’deki<\/em> 0,2001 birimlik art\u0131\u015fla ili\u015fkili oldu\u011fu anlam\u0131na gelir. Bu durumda a\u011f\u0131rl\u0131ktaki bir poundluk art\u0131\u015f, boyda 0,2001 in\u00e7lik bir art\u0131\u015fla ili\u015fkilidir.<\/span><\/p>\n

En k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisi nas\u0131l kullan\u0131l\u0131r?<\/span><\/strong><\/h2>\n

Bu en k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisini kullanarak a\u015fa\u011f\u0131daki gibi sorular\u0131 yan\u0131tlayabiliriz:<\/span><\/p>\n

170 kilo a\u011f\u0131rl\u0131\u011f\u0131ndaki birinin boyunun ne kadar olmas\u0131n\u0131 beklemeliyiz?<\/em><\/span><\/p>\n

Bu soruyu cevaplamak i\u00e7in, x i\u00e7in regresyon \u00e7izgimize 170’i ekleyip y’yi \u00e7\u00f6zebiliriz:<\/span><\/p>\n

\u0177 = 32,7830 + 0,2001(170) = 66,8 in\u00e7<\/strong><\/span><\/p>\n

150 kilo a\u011f\u0131rl\u0131\u011f\u0131ndaki birinin boyunun ne kadar olmas\u0131n\u0131 beklemeliyiz?<\/em><\/span><\/p>\n

Bu soruyu cevaplamak i\u00e7in regresyon \u00e7izgimize x i\u00e7in 150 ekleyebilir ve y’yi \u00e7\u00f6zebiliriz:<\/span><\/p>\n

\u0177 = 32,7830 + 0,2001(150) = 62,798 in\u00e7<\/strong><\/span><\/p>\n

Dikkat:<\/strong> Bunun gibi sorular\u0131 yan\u0131tlamak i\u00e7in regresyon denklemi kullan\u0131rken, yorday\u0131c\u0131 de\u011fi\u015fken i\u00e7in yaln\u0131zca veri k\u00fcmesindeki yorday\u0131c\u0131 de\u011fi\u015fkenin aral\u0131\u011f\u0131 i\u00e7indeki de\u011ferleri kulland\u0131\u011f\u0131n\u0131zdan emin olun. En k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisini olu\u015fturmak i\u00e7in kulland\u0131\u011f\u0131m\u0131z orijin. \u00d6rne\u011fin veri setimizdeki a\u011f\u0131rl\u0131klar 140 ila 212 pound aras\u0131nda de\u011fi\u015fiyordu. Bu nedenle, a\u011f\u0131rl\u0131k 140 ila 212 pound aras\u0131nda oldu\u011funda beklenen boyla ilgili sorular\u0131 yan\u0131tlamak mant\u0131kl\u0131 olur.<\/em><\/span><\/p>\n

Belirleme katsay\u0131s\u0131<\/strong><\/h2>\n

En k\u00fc\u00e7\u00fck kareler regresyon \u00e7izgisinin verilere ne kadar iyi uydu\u011funu \u00f6l\u00e7menin bir yolu, R2<\/sup> ile g\u00f6sterilen belirleme katsay\u0131s\u0131n\u0131<\/strong> kullanmakt\u0131r.<\/span><\/p>\n

Belirleme katsay\u0131s\u0131, yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan a\u00e7\u0131klanabilen yan\u0131t de\u011fi\u015fkenindeki varyans\u0131n oran\u0131d\u0131r.<\/span><\/p>\n

Belirleme katsay\u0131s\u0131 0 ila 1 aras\u0131nda de\u011fi\u015febilir. 0 de\u011feri, yan\u0131t de\u011fi\u015fkeninin yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan hi\u00e7bir \u015fekilde a\u00e7\u0131klanamayaca\u011f\u0131n\u0131 g\u00f6sterir. 1 de\u011feri, yan\u0131t de\u011fi\u015fkeninin yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan hatas\u0131z olarak m\u00fckemmel bir \u015fekilde a\u00e7\u0131klanabilece\u011fini g\u00f6sterir.<\/span><\/p>\n

0 ile 1 aras\u0131ndaki bir<\/span> R2,<\/sup> yan\u0131t de\u011fi\u015fkeninin yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan ne \u00f6l\u00e7\u00fcde a\u00e7\u0131klanabilece\u011fini g\u00f6sterir. \u00d6rne\u011fin, 0,2’lik bir R2<\/sup> , yan\u0131t de\u011fi\u015fkenindeki varyans\u0131n %20’sinin yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan a\u00e7\u0131klanabilece\u011fini g\u00f6sterir; 0,77’lik bir R2,<\/sup> yan\u0131t de\u011fi\u015fkenindeki varyans\u0131n %77’sinin yorday\u0131c\u0131 de\u011fi\u015fken taraf\u0131ndan a\u00e7\u0131klanabilece\u011fini g\u00f6sterir.<\/span><\/p>\n

\u00d6nceki sonucumuzda 0,9311’lik bir R2<\/sup> elde etti\u011fimize dikkat edin; bu, boydaki de\u011fi\u015fkenli\u011fin %93,11’inin a\u011f\u0131rl\u0131k belirleyici de\u011fi\u015fken taraf\u0131ndan a\u00e7\u0131klanabilece\u011fini g\u00f6sterir:<\/span> <\/p>\n

\"Do\u011frusal<\/p>\n

Bu bize a\u011f\u0131rl\u0131\u011f\u0131n boy i\u00e7in \u00e7ok iyi bir g\u00f6sterge oldu\u011funu s\u00f6yler.<\/span><\/p>\n

Do\u011frusal Regresyon Varsay\u0131mlar\u0131<\/span><\/strong><\/h2>\n

Do\u011frusal regresyon modelinin sonu\u00e7lar\u0131n\u0131n ge\u00e7erli ve g\u00fcvenilir olmas\u0131 i\u00e7in a\u015fa\u011f\u0131daki d\u00f6rt varsay\u0131m\u0131n kar\u015f\u0131land\u0131\u011f\u0131n\u0131 do\u011frulamam\u0131z gerekir:<\/span><\/p>\n

1. Do\u011frusal ili\u015fki:<\/strong> Ba\u011f\u0131ms\u0131z de\u011fi\u015fken x ile ba\u011f\u0131ml\u0131 de\u011fi\u015fken y aras\u0131nda do\u011frusal bir ili\u015fki vard\u0131r.<\/span><\/p>\n

2. Ba\u011f\u0131ms\u0131zl\u0131k:<\/strong> Art\u0131klar ba\u011f\u0131ms\u0131zd\u0131r. \u00d6zellikle zaman serisi verilerinde ard\u0131\u015f\u0131k art\u0131klar aras\u0131nda bir korelasyon yoktur.<\/span><\/p>\n

3. Homoskedastisite:<\/strong> Art\u0131klar x’in her seviyesinde sabit bir varyansa sahiptir.<\/span><\/p>\n

4. Normallik:<\/strong> Model art\u0131klar\u0131 normal da\u011f\u0131l\u0131ma sahiptir.<\/span><\/p>\n

Bu varsay\u0131mlardan bir veya daha fazlas\u0131 kar\u015f\u0131lanmazsa, do\u011frusal regresyonumuzun sonu\u00e7lar\u0131 g\u00fcvenilmez ve hatta yan\u0131lt\u0131c\u0131 olabilir.<\/span><\/p>\n

Her bir varsay\u0131m\u0131n a\u00e7\u0131klamas\u0131, varsay\u0131m\u0131n kar\u015f\u0131lan\u0131p kar\u015f\u0131lanmad\u0131\u011f\u0131n\u0131n nas\u0131l belirlenece\u011fi ve varsay\u0131m kar\u015f\u0131lanmazsa ne yap\u0131laca\u011f\u0131 hakk\u0131nda bilgi i\u00e7in bu makaleye<\/a> bak\u0131n.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Basit do\u011frusal regresyon, iki de\u011fi\u015fken (x ve y) aras\u0131ndaki ili\u015fkiyi anlamak i\u00e7in kullanabilece\u011finiz istatistiksel bir y\u00f6ntemdir. Bir de\u011fi\u015fken olan x , yorday\u0131c\u0131 de\u011fi\u015fken olarak bilinir. Di\u011fer de\u011fi\u015fken, y , yan\u0131t de\u011fi\u015fkeni olarak bilinir. \u00d6rne\u011fin, yedi ki\u015finin a\u011f\u0131rl\u0131\u011f\u0131n\u0131 ve boyunu i\u00e7eren a\u015fa\u011f\u0131daki veri setine sahip oldu\u011fumuzu varsayal\u0131m: A\u011f\u0131rl\u0131k belirleyici de\u011fi\u015fken olsun ve boy da yan\u0131t de\u011fi\u015fkeni […]<\/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-418","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nBasit Do\u011frusal Regresyona Giri\u015f - Statoryaller<\/title>\n<meta name=\"description\" content=\"Resmi bir tan\u0131m ve bir \u00f6rnek i\u00e7eren do\u011frusal regresyona basit bir giri\u015f.\" \/>\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\/dogrusal-regresyon\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Basit Do\u011frusal Regresyona Giri\u015f - Statoryaller\" \/>\n<meta property=\"og:description\" content=\"Resmi bir tan\u0131m ve bir \u00f6rnek i\u00e7eren do\u011frusal regresyona basit bir giri\u015f.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-30T05:00:57+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/poids_hauteur1.jpg\" \/>\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=\"5 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/\",\"url\":\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/\",\"name\":\"Basit Do\u011frusal Regresyona Giri\u015f - Statoryaller\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/tr\/#website\"},\"datePublished\":\"2023-07-30T05:00:57+00:00\",\"dateModified\":\"2023-07-30T05:00:57+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\"},\"description\":\"Resmi bir tan\u0131m ve bir \u00f6rnek i\u00e7eren do\u011frusal regresyona basit bir giri\u015f.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/tr\/dogrusal-regresyon\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Ev\",\"item\":\"https:\/\/statorials.org\/tr\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Basit do\u011frusal regresyona giri\u015f\"}]},{\"@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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