Bir veri k\u00fcmesindeki de\u011fi\u015fkenler aras\u0131nda var olan do\u011frusal ili\u015fkilerin g\u00fcc\u00fcn\u00fc anlaman\u0131n h\u0131zl\u0131 bir yolunu sa\u011flar.<\/span><\/p>\n Belirli bir veri k\u00fcmesi i\u00e7in bir korelasyon matrisi olu\u015fturmak amac\u0131yla SAS’ta PROC CORR<\/strong> deyimini kullanabilirsiniz:<\/span><\/p>\n Varsay\u0131lan olarak bu, veri k\u00fcmesindeki t\u00fcm say\u0131sal de\u011fi\u015fkenler aras\u0131ndaki korelasyon katsay\u0131lar\u0131n\u0131 g\u00f6r\u00fcnt\u00fcleyen bir matris olu\u015fturacakt\u0131r.<\/span><\/p>\n Korelasyon matrisine yaln\u0131zca belirli de\u011fi\u015fkenleri dahil etmek i\u00e7in VAR<\/strong> ifadesini kullanabilirsiniz:<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, SAS’ta bir korelasyon matrisinin nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n SAS’ta \u00e7e\u015fitli basketbol oyuncular\u0131 hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki veri k\u00fcmesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span> <\/p>\n Varsay\u0131lan olarak veri k\u00fcmesindeki her say\u0131sal de\u011fi\u015fkeni i\u00e7eren bir korelasyon matrisi olu\u015fturmak i\u00e7in PROC CORR<\/strong> ifadesini kullanabiliriz:<\/span> <\/p>\n \u00c7\u0131kt\u0131, ilk tablodaki say\u0131sal de\u011fi\u015fkenlerin \u00f6zet istatistiklerini bir korelasyon matrisiyle birlikte g\u00f6r\u00fcnt\u00fcler.<\/span><\/p>\n \u201cTak\u0131m\u201d de\u011fi\u015fkeninin say\u0131sal bir de\u011fi\u015fken olmad\u0131\u011f\u0131 i\u00e7in korelasyon matrisine dahil edilmedi\u011fine dikkat edin.<\/span><\/p>\n Korelasyon matrisi de\u011ferlerinin nas\u0131l yorumlanaca\u011f\u0131 a\u015fa\u011f\u0131da a\u00e7\u0131klanm\u0131\u015ft\u0131r:<\/span><\/p>\n (1)<\/strong> Asistler<\/strong> ve ribaundlar<\/strong> aras\u0131ndaki Pearson korelasyon katsay\u0131s\u0131 (r) -0,24486’d\u0131r<\/strong> . Kar\u015f\u0131l\u0131k gelen p de\u011feri 0,5589’dur<\/strong> .<\/span><\/p>\n r’nin s\u0131f\u0131rdan k\u00fc\u00e7\u00fck olmas\u0131 bize bu iki de\u011fi\u015fken aras\u0131nda negatif do\u011frusal bir ili\u015fki oldu\u011funu s\u00f6yler. Ancak p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck olmad\u0131\u011f\u0131 i\u00e7in bu korelasyon istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n (2)<\/strong> Asistler<\/strong> ve say\u0131lar<\/b> aras\u0131ndaki Pearson korelasyon katsay\u0131s\u0131 (r) -0,32957’dir<\/strong> . Kar\u015f\u0131l\u0131k gelen p de\u011feri 0,4253’t\u00fcr<\/strong> .<\/span><\/p>\n Bu iki de\u011fi\u015fken aras\u0131nda negatif do\u011frusal bir ili\u015fki vard\u0131r ancak istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n (3)<\/strong> Ribaundlar<\/b> ile say\u0131lar<\/b> aras\u0131ndaki Pearson korelasyon katsay\u0131s\u0131 (r) -0,52209’dur<\/strong> . Kar\u015f\u0131l\u0131k gelen p de\u011feri 0,1844’t\u00fcr<\/strong> .<\/span><\/p>\n Bu iki de\u011fi\u015fken aras\u0131nda negatif do\u011frusal bir ili\u015fki vard\u0131r ancak istatistiksel olarak anlaml\u0131 de\u011fildir.<\/span><\/p>\n Korelasyon matrisine yaln\u0131zca belirli say\u0131sal de\u011fi\u015fkenleri dahil etmek i\u00e7in VAR<\/strong> ifadesini de kullanabilece\u011fimizi unutmay\u0131n:<\/span> <\/p>\n Bu korelasyon matrisine yaln\u0131zca asist<\/strong> ve ribaund<\/strong> de\u011fi\u015fkenlerinin dahil edildi\u011fini unutmay\u0131n.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde SAS’ta di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n SAS’ta Da\u011f\u0131l\u0131m Grafi\u011fi Matrisi Nas\u0131l Olu\u015fturulur<\/a> Korelasyon matrisi, bir veri setindeki de\u011fi\u015fkenler aras\u0131ndaki korelasyon katsay\u0131lar\u0131n\u0131 g\u00f6steren kare bir tablodur. Bir veri k\u00fcmesindeki de\u011fi\u015fkenler aras\u0131nda var olan do\u011frusal ili\u015fkilerin g\u00fcc\u00fcn\u00fc anlaman\u0131n h\u0131zl\u0131 bir yolunu sa\u011flar. Belirli bir veri k\u00fcmesi i\u00e7in bir korelasyon matrisi olu\u015fturmak amac\u0131yla SAS’ta PROC CORR deyimini kullanabilirsiniz: \/*create correlation matrix using all numeric variables in my_data*\/ proc corr data […]<\/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-4532","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \/*create correlation matrix using all numeric variables in my_data*\/\n<\/span>proc corr<\/span> data<\/span> =my_data;\nrun<\/span> ;<\/strong><\/span><\/pre>\n \/*create correlation matrix using only var1, var2 and var3 in my_data*\/\n<\/span>proc corr<\/span> data<\/span> =my_data;\n var<\/span> var1, var2, var3;\nrun<\/span> ;<\/strong><\/span><\/pre>\n \u00d6rnek: SAS’ta Korelasyon Matrisi Olu\u015fturma<\/strong><\/h2>\n
\/*create dataset*\/\n<\/span>data<\/span> my_data;\n input<\/span> team $ assists rebounds points;\n datalines<\/span> ;\nA 4 12 22\nA 5 14 24\nA 5 13 26\nA 6 7 26\nB 7 8 29\nB 8 8 32\nB 8 9 20\nB 10 13 14\n;\nrun<\/span> ;\n\n\/*view dataset*\/\n<\/span>proc print<\/span> data<\/span> =my_data;<\/strong><\/span> <\/pre>\n![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/corrmat1.png\")
<\/p>\n \/*create correlation matrix using all numeric variables in my_data*\/\n<\/span>proc corr<\/span> data<\/span> =my_data;\nrun<\/span> ;<\/strong><\/span> <\/pre>\n![\"SAS'taki](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/corrmat2.png\")
<\/p>\n \/*create correlation matrix using only assists and rebounds variables*\/\n<\/span>proc corr<\/span> data<\/span> =my_data;\n var<\/span> assists rebounds;\nrun<\/span> ;<\/strong><\/span> <\/pre>\n![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/corrmat3.png\")
<\/p>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
SAS’ta PivotTable’lar Nas\u0131l Olu\u015fturulur<\/a>
SAS’ta Varyans Enflasyon Fakt\u00f6r\u00fc (VIF) nas\u0131l hesaplan\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"