<\/p>\n
Bir\u00e7ok istatistiksel test ( tek y\u00f6nl\u00fc ANOVA<\/a> veya iki y\u00f6nl\u00fc ANOVA<\/a> gibi), birden fazla grup aras\u0131ndaki varyans\u0131n e\u015fit oldu\u011funu varsayar.<\/span><\/p>\n Bu hipotezi resmi olarak test etmenin bir yolu, iki veya daha fazla grup aras\u0131ndaki varyans\u0131n e\u015fit olup olmad\u0131\u011f\u0131n\u0131 test eden Levene testini<\/strong> kullanmakt\u0131r.<\/span><\/p>\n Bu test a\u015fa\u011f\u0131daki varsay\u0131mlara dayanmaktad\u0131r:<\/span><\/p>\n S\u0131f\u0131r hipotezi (H 0<\/sub> )<\/strong> : Gruplar aras\u0131ndaki varyans e\u015fittir.<\/span><\/p>\n Alternatif hipotez ( HA<\/sub> )<\/strong> : Gruplar aras\u0131ndaki varyans e\u015fit de\u011fildir<\/em> .<\/span><\/p>\n Testin p de\u011feri se\u00e7ilen anlaml\u0131l\u0131k d\u00fczeyinden k\u00fc\u00e7\u00fckse, s\u0131f\u0131r hipotezini reddedebilir ve gruplar aras\u0131ndaki varyans\u0131n e\u015fit olmad\u0131\u011f\u0131n\u0131 s\u00f6yleyecek yeterli kan\u0131t\u0131m\u0131z oldu\u011fu sonucuna varabiliriz.<\/span><\/p>\n R’de Levene testini ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanan ara\u00e7<\/strong> k\u00fct\u00fcphanesindeki leveneTest()<\/strong> fonksiyonunu kullanabiliriz:<\/span><\/p>\n leveneTest (yan\u0131t de\u011fi\u015fkeni ~ grup de\u011fi\u015fkeni, veri = veri)<\/span><\/p>\n \u00d6rnek olarak, insanlar\u0131n \u00fc\u00e7 farkl\u0131 kilo verme program\u0131yla ne kadar kilo verdiklerini g\u00f6steren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesini d\u00fc\u015f\u00fcn\u00fcn:<\/span><\/p>\n Bu \u00fc\u00e7 program aras\u0131ndaki kilo kayb\u0131 varyans\u0131n\u0131n e\u015fit olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in leveneTest()<\/strong> fonksiyonunu kullanabilir ve anlaml\u0131l\u0131k d\u00fczeyi olarak 0,05’i kullanabiliriz:<\/span><\/p>\n Testin p de\u011feri 0,01862<\/strong> olup, bizim anlaml\u0131l\u0131k seviyemiz olan 0,05’in alt\u0131ndad\u0131r.<\/span><\/p>\n Dolay\u0131s\u0131yla s\u0131f\u0131r hipotezini reddediyoruz ve \u00fc\u00e7 grup aras\u0131ndaki varyans\u0131n e\u015fit olmad\u0131\u011f\u0131<\/em> sonucuna var\u0131yoruz.<\/span><\/p>\n Levene testini yaparak \u00fc\u00e7 grup aras\u0131ndaki varyanslar\u0131n e\u015fit olmad\u0131\u011f\u0131n\u0131 biliyoruz.<\/span><\/p>\n Bu testi ger\u00e7ekle\u015ftirmenin yan\u0131 s\u0131ra, \u00fc\u00e7 grubun her biri i\u00e7in a\u011f\u0131rl\u0131k kayb\u0131 da\u011f\u0131l\u0131m\u0131n\u0131 g\u00f6steren kutu grafikleri olu\u015fturabiliriz, b\u00f6ylece Levene testinin varyanslar\u0131n e\u015fitli\u011fine ili\u015fkin s\u0131f\u0131r hipotezini neden reddetti\u011fini g\u00f6rsel olarak anlayabiliriz.<\/span><\/p>\n C program\u0131ndaki kat\u0131l\u0131mc\u0131lar i\u00e7in kilo kayb\u0131ndaki varyans\u0131n di\u011fer iki programa g\u00f6re \u00f6nemli \u00f6l\u00e7\u00fcde daha y\u00fcksek oldu\u011funu g\u00f6rebiliriz.<\/span><\/p>\n Bu nedenle Levene testinin, varyanslar\u0131n \u00fc\u00e7 grup aras\u0131nda e\u015fit oldu\u011funa ili\u015fkin s\u0131f\u0131r hipotezini reddetmesi mant\u0131kl\u0131d\u0131r.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Levene testinin farkl\u0131 istatistiksel yaz\u0131l\u0131mlarda nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Excel’de Levene testi nas\u0131l yap\u0131l\u0131r<\/a> Bir\u00e7ok istatistiksel test ( tek y\u00f6nl\u00fc ANOVA veya iki y\u00f6nl\u00fc ANOVA gibi), birden fazla grup aras\u0131ndaki varyans\u0131n e\u015fit oldu\u011funu varsayar. Bu hipotezi resmi olarak test etmenin bir yolu, iki veya daha fazla grup aras\u0131ndaki varyans\u0131n e\u015fit olup olmad\u0131\u011f\u0131n\u0131 test eden Levene testini kullanmakt\u0131r. Bu test a\u015fa\u011f\u0131daki varsay\u0131mlara dayanmaktad\u0131r: S\u0131f\u0131r hipotezi (H 0 ) : Gruplar […]<\/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-510","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n R’de Levene testi nas\u0131l yap\u0131l\u0131r?<\/strong><\/span><\/h2>\n
#make this example reproducible\n<\/span>set. seeds<\/span> (0)\n\n#create data frame\n<\/span>data <- data. frame<\/span> (program = rep(c(\"A\", \"B\", \"C\"), each = 30<\/span> ),\n weight_loss = c(runif(30, 0, 3),\n runif(30, 0, 5),\n runif(30, 1, 7)))\n\n#view first six rows of data frame\n<\/span>head(data)\n\n# program weight_loss\n#1 A 2.6900916\n#2 A 0.7965260\n#3 A 1.1163717\n#4 A 1.7185601\n#5 A 2.7246234\n#6 A 0.6050458<\/strong><\/pre>\n #load car package\n<\/span>library<\/span> (car)\n\n#conduct Levene's Test for equality of variances\n<\/span>leveneTest(weight_loss ~ program, data = data)\n\n#Levene's Test for Homogeneity of Variance (center = median)\n# Df F value Pr(>F) \n#group 2 4.1716 0.01862 *\n#87 \n#---\n#Significant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/strong><\/pre>\n Varyanslardaki farkl\u0131l\u0131klar\u0131 g\u00f6rselle\u015ftirin<\/strong><\/span><\/h3>\n
boxplot(weight_loss ~ program,\n data = data,\n main = \"Weight Loss Distribution by Program\",\n xlab = \"Program\",\n ylab = \"Weight Loss\",\n col = \"steelblue\",\n border = \"black\")<\/strong><\/pre>\n
Ek kaynaklar<\/strong><\/span><\/h3>\n
Python’da Levene testi nas\u0131l yap\u0131l\u0131r?<\/a>
SPSS’de Levene Testi Nas\u0131l Yap\u0131l\u0131r?<\/a>
Stata’da Levene testi nas\u0131l yap\u0131l\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"