<\/p>\n
\u0130statistikte, iki de\u011fi\u015fken aras\u0131ndaki do\u011frusal ili\u015fkiyi \u00f6l\u00e7mek i\u00e7in s\u0131kl\u0131kla Pearson korelasyon katsay\u0131s\u0131n\u0131<\/a> kullan\u0131r\u0131z.<\/span><\/p>\n Ancak bazen \u00fc\u00e7\u00fcnc\u00fc bir de\u011fi\u015fkeni kontrol ederken<\/strong> iki de\u011fi\u015fken aras\u0131ndaki ili\u015fkiyi anlamak isteriz.<\/span><\/p>\n \u00d6rne\u011fin, \u00f6\u011frencinin s\u0131n\u0131ftaki mevcut notunu kontrol ederken, \u00f6\u011frencinin ders \u00e7al\u0131\u015fma saati ile final s\u0131nav notu aras\u0131ndaki ili\u015fkiyi \u00f6l\u00e7mek istedi\u011fimizi varsayal\u0131m.<\/span><\/p>\n Bu durumda \u00e7al\u0131\u015f\u0131lan saat ile final s\u0131nav notu aras\u0131ndaki ili\u015fkiyi \u00f6l\u00e7mek i\u00e7in k\u0131smi korelasyonu<\/strong> kullanabiliriz.<\/span><\/p>\n Bu e\u011fitimde R’de k\u0131smi bir korelasyonun nas\u0131l hesaplanaca\u011f\u0131 a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n 10 \u00f6\u011frencinin mevcut notunu, \u00e7al\u0131\u015f\u0131lan toplam saati ve final s\u0131nav notunu g\u00f6steren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n Veri \u00e7er\u00e7evesindeki de\u011fi\u015fkenlerin her ikili kombinasyonu aras\u0131ndaki k\u0131smi korelasyonu hesaplamak i\u00e7in ppcor k\u00fct\u00fcphanesindeki<\/a> pcor()<\/strong> fonksiyonunu kullanabiliriz:<\/span><\/p>\n Sonucun nas\u0131l yorumlanaca\u011f\u0131 a\u015fa\u011f\u0131da a\u00e7\u0131klanm\u0131\u015ft\u0131r:<\/span><\/p>\n \u00c7al\u0131\u015f\u0131lan saat ile final s\u0131nav notu aras\u0131ndaki k\u0131smi korelasyon:<\/strong><\/span><\/p>\n \u00c7al\u0131\u015f\u0131lan saat ile final s\u0131nav\u0131 notu aras\u0131ndaki k\u0131smi korelasyon 0,191’dir<\/strong> ve bu k\u00fc\u00e7\u00fck bir pozitif korelasyonu temsil eder. \u00c7al\u0131\u015fma saatlerinin say\u0131s\u0131 artt\u0131k\u00e7a, mevcut notun sabit kald\u0131\u011f\u0131 varsay\u0131larak s\u0131nav puanlar\u0131 da artma e\u011filimindedir.<\/span><\/p>\n Bu k\u0131smi korelasyonun p de\u011feri 0,623’t\u00fcr<\/strong> ve \u03b1 = 0,05’te istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n Mevcut not ile final s\u0131nav\u0131 notu aras\u0131ndaki k\u0131smi korelasyon:<\/strong><\/span><\/p>\n Mevcut not ile final s\u0131nav\u0131 notu aras\u0131ndaki k\u0131smi korelasyon 0,736’d\u0131r<\/strong> ve bu da g\u00fc\u00e7l\u00fc bir pozitif korelasyonu temsil eder. Mevcut not artt\u0131k\u00e7a, \u00e7al\u0131\u015f\u0131lan saat say\u0131s\u0131n\u0131n sabit kald\u0131\u011f\u0131 varsay\u0131larak s\u0131nav puanlar\u0131 da artma e\u011filimindedir.<\/span><\/p>\n Bu k\u0131smi korelasyonun p de\u011feri 0,024’t\u00fcr<\/strong> ve bu, \u03b1 = 0,05’te istatistiksel olarak anlaml\u0131d\u0131r.<\/span><\/p>\n Mevcut not ile \u00e7al\u0131\u015f\u0131lan saat aras\u0131ndaki k\u0131smi korelasyon:<\/strong><\/span><\/p>\n Mevcut not, \u00e7al\u0131\u015f\u0131lan saat ve final s\u0131nav\u0131 notu aras\u0131ndaki k\u0131smi korelasyon -0,311<\/strong> olup, bu hafif bir negatif korelasyonu temsil etmektedir. Final s\u0131nav notunun sabit kald\u0131\u011f\u0131 varsay\u0131larak, mevcut not artt\u0131k\u00e7a final s\u0131nav notu d\u00fc\u015fme e\u011filimi g\u00f6sterir.<\/span><\/p>\n Bu k\u0131smi korelasyonun p de\u011feri<\/a> 0,415’tir<\/strong> ve \u03b1 = 0,05’te istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n Sonu\u00e7 ayr\u0131ca bize k\u0131smi korelasyonu hesaplamak i\u00e7in kullan\u0131lan y\u00f6ntemin \u201cPearson\u201d oldu\u011funu da s\u00f6yl\u00fcyor.<\/span><\/p>\n PCor()<\/strong> i\u015flevinde, korelasyonlar\u0131 hesaplamak i\u00e7in alternatif y\u00f6ntemler olarak “kendall” veya “pearson”u da belirtebiliriz.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde R’de di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n R’de Spearman s\u0131ralama korelasyonu nas\u0131l hesaplan\u0131r<\/a> \u0130statistikte, iki de\u011fi\u015fken aras\u0131ndaki do\u011frusal ili\u015fkiyi \u00f6l\u00e7mek i\u00e7in s\u0131kl\u0131kla Pearson korelasyon katsay\u0131s\u0131n\u0131 kullan\u0131r\u0131z. Ancak bazen \u00fc\u00e7\u00fcnc\u00fc bir de\u011fi\u015fkeni kontrol ederken iki de\u011fi\u015fken aras\u0131ndaki ili\u015fkiyi anlamak isteriz. \u00d6rne\u011fin, \u00f6\u011frencinin s\u0131n\u0131ftaki mevcut notunu kontrol ederken, \u00f6\u011frencinin ders \u00e7al\u0131\u015fma saati ile final s\u0131nav notu aras\u0131ndaki ili\u015fkiyi \u00f6l\u00e7mek istedi\u011fimizi varsayal\u0131m. Bu durumda \u00e7al\u0131\u015f\u0131lan saat ile final s\u0131nav notu aras\u0131ndaki […]<\/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-914","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: R’de k\u0131smi korelasyon<\/strong><\/span><\/h2>\n
#create data frame<\/span>\ndf <- data. frame<\/span> (currentGrade = c(82, 88, 75, 74, 93, 97, 83, 90, 90, 80),\n hours = c(4, 3, 6, 5, 4, 5, 8, 7, 4, 6),\n examScore = c(88, 85, 76, 70, 92, 94, 89, 85, 90, 93))\n\n#view data frame\n<\/span>df\n\n currentGrade hours examScore\n1 82 4 88\n2 88 3 85\n3 75 6 76\n4 74 5 70\n5 93 4 92\n6 97 5 94\n7 83 8 89\n8 90 7 85\n9 90 4 90\n10 80 6 93\n<\/strong><\/pre>\n library<\/span> (ppcor)<\/span>\n\n#calculate partial correlations<\/span>\npcor(df)\n\n$estimate\n currentGrade hours examScore\ncurrentGrade 1.0000000 -0.3112341 0.7355673\nhours -0.3112341 1.0000000 0.1906258\nexamScore 0.7355673 0.1906258 1.0000000\n\n$p.value\n currentGrade hours examScore\ncurrentGrade 0.00000000 0.4149353 0.02389896\nhours 0.41493532 0.0000000 0.62322848\nexamScore 0.02389896 0.6232285 0.00000000\n\n$statistic\n currentGrade hours examScore\ncurrentGrade 0.0000000 -0.8664833 2.8727185\nhours -0.8664833 0.0000000 0.5137696\nexamScore 2.8727185 0.5137696 0.0000000\n\n$n\n[1] 10\n\n$gp\n[1] 1\n\n$method\n[1] \"pearson\"\n<\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
R’de \u00e7apraz korelasyon nas\u0131l hesaplan\u0131r<\/a>
R’de kayan korelasyon nas\u0131l hesaplan\u0131r<\/a>
R’de nokta-\u00e7ift serili korelasyon nas\u0131l hesaplan\u0131r<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"