<\/p>\n
\u0130statistikte korelasyon<\/strong> , iki de\u011fi\u015fken aras\u0131ndaki ili\u015fkinin g\u00fcc\u00fcn\u00fc ve y\u00f6n\u00fcn\u00fc ifade eder. Bir korelasyon katsay\u0131s\u0131n\u0131n de\u011feri, a\u015fa\u011f\u0131daki yorumlara g\u00f6re -1 ile 1 aras\u0131nda de\u011fi\u015febilir:<\/span><\/p>\n \u00d6zel bir korelasyon t\u00fcr\u00fc, iki s\u0131ral\u0131 de\u011fi\u015fken aras\u0131ndaki korelasyonu \u00f6l\u00e7mek i\u00e7in kullan\u0131lan Spearman’\u0131n s\u0131ra korelasyonu<\/strong> olarak adland\u0131r\u0131l\u0131r. (\u00f6rne\u011fin, bir \u00f6\u011frencinin matematik s\u0131nav\u0131 puan\u0131n\u0131n, s\u0131n\u0131ftaki fen bilimleri s\u0131nav\u0131 puan\u0131na g\u00f6re s\u0131ralamas\u0131).<\/span><\/p>\n R’deki iki de\u011fi\u015fken aras\u0131ndaki Spearman s\u0131ra korelasyonunu hesaplamak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler bu fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, R’deki iki vekt\u00f6r aras\u0131ndaki Spearman s\u0131ra korelasyonunun nas\u0131l hesaplanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/span><\/p>\n Sonu\u00e7tan Spearman s\u0131ra korelasyonunun -0,41818<\/strong> ve buna kar\u015f\u0131l\u0131k gelen p de\u011ferinin 0,2324<\/strong> oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n Bu, iki vekt\u00f6r aras\u0131nda negatif bir korelasyon oldu\u011funu g\u00f6sterir.<\/span><\/p>\n Ancak korelasyonun p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck olmad\u0131\u011f\u0131 i\u00e7in korelasyon istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, bir veri \u00e7er\u00e7evesindeki iki s\u00fctun aras\u0131ndaki Spearman s\u0131ra korelasyonunun nas\u0131l hesaplanaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Sonu\u00e7tan Spearman s\u0131ra korelasyonunun 0,7818<\/strong> ve buna kar\u015f\u0131l\u0131k gelen p de\u011ferinin 0,01165<\/strong> oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n Bu, iki vekt\u00f6r aras\u0131nda g\u00fc\u00e7l\u00fc bir pozitif korelasyon oldu\u011funu g\u00f6sterir.<\/span><\/p>\n Korelasyonun p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck oldu\u011fundan korelasyon istatistiksel olarak anlaml\u0131d\u0131r.<\/span><\/p>\n R’de k\u0131smi korelasyon nas\u0131l hesaplan\u0131r<\/a> \u0130statistikte korelasyon , iki de\u011fi\u015fken aras\u0131ndaki ili\u015fkinin g\u00fcc\u00fcn\u00fc ve y\u00f6n\u00fcn\u00fc ifade eder. Bir korelasyon katsay\u0131s\u0131n\u0131n de\u011feri, a\u015fa\u011f\u0131daki yorumlara g\u00f6re -1 ile 1 aras\u0131nda de\u011fi\u015febilir: -1: iki de\u011fi\u015fken aras\u0131nda m\u00fckemmel bir negatif ili\u015fki 0: iki de\u011fi\u015fken aras\u0131nda ili\u015fki yok 1: iki de\u011fi\u015fken aras\u0131nda m\u00fckemmel bir pozitif ili\u015fki \u00d6zel bir korelasyon t\u00fcr\u00fc, iki s\u0131ral\u0131 de\u011fi\u015fken aras\u0131ndaki korelasyonu […]<\/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-2018","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n\n
corr <- cor. test<\/span> (x, y, method = ' spearman<\/span> ')\n<\/strong><\/pre>\n \u00d6rnek 1: Spearman s\u0131ralar\u0131n\u0131n vekt\u00f6rler aras\u0131ndaki korelasyonu<\/strong><\/span><\/h3>\n
#define data\n<\/span>x <- c(70, 78, 90, 87, 84, 86, 91, 74, 83, 85)\ny <- c(90, 94, 79, 86, 84, 83, 88, 92, 76, 75)\n\n#calculate Spearman rank correlation between x and y\n<\/span>horn. test<\/span> (x, y, method = ' spearman<\/span> ')\n\n\tSpearman's rank correlation rho\n\ndata: x and y\nS = 234, p-value = 0.2324\nalternative hypothesis: true rho is not equal to 0\nsample estimates:\n rho \n-0.4181818<\/strong><\/span><\/pre>\n \u00d6rnek 2: Veri \u00e7er\u00e7evesindeki s\u00fctunlar aras\u0131ndaki Spearman s\u0131ra korelasyonu<\/strong><\/span><\/h3>\n
#define data frame\n<\/span>df <- data. frame<\/span> (team=c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'),\n points=c(67, 70, 75, 78, 73, 89, 84, 99, 90, 91),\n assists=c(22, 27, 30, 23, 25, 31, 38, 35, 34, 32))\n\n#calculate Spearman rank correlation between x and y\n<\/span>horn. test<\/span> (df$points, df$assists, method = 'spearman')\n\n\tSpearman's rank correlation rho\n\ndata: df$points and df$assists\nS = 36, p-value = 0.01165\nalternative hypothesis: true rho is not equal to 0\nsample estimates:\n rho \n0.7818182 \n<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
R’de otokorelasyon nas\u0131l hesaplan\u0131r<\/a>
R’de kayan korelasyon nas\u0131l hesaplan\u0131r<\/a>
Spearman korelasyonunun APA format\u0131nda raporlanmas\u0131<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"