<\/p>\n
R’deki aov()<\/strong> ve anova()<\/strong> i\u015flevleri benzer g\u00f6r\u00fcnse de asl\u0131nda bunlar\u0131 iki farkl\u0131 senaryoda kullan\u0131yoruz.<\/span><\/p>\n Bir ANOVA modeline s\u0131\u011fd\u0131rmak ve sonu\u00e7lar\u0131 bir ANOVA \u00f6zet tablosunda g\u00f6r\u00fcnt\u00fclemek istedi\u011fimizde aov()<\/strong> kullan\u0131r\u0131z.<\/span><\/p>\n Belirli bir katsay\u0131lar dizisine sahip bir regresyon modelinin, yaln\u0131zca bir katsay\u0131lar alt k\u00fcmesine sahip bir modele g\u00f6re \u00f6nemli \u00f6l\u00e7\u00fcde daha iyi bir uyum sa\u011flay\u0131p sa\u011flamad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in i\u00e7 i\u00e7e regresyon modellerinin uyumunu kar\u015f\u0131la\u015ft\u0131rmak istedi\u011fimizde anova()<\/strong> kullan\u0131r\u0131z.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnekler her bir fonksiyonun pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6stermektedir.<\/span><\/p>\n Diyelim ki \u00fc\u00e7 farkl\u0131 egzersiz program\u0131n\u0131n kilo kayb\u0131 \u00fczerinde farkl\u0131 bir etkiye sahip olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in tek y\u00f6nl\u00fc bir ANOVA<\/a> yapmak istiyoruz.<\/span><\/p>\n Bir ay boyunca Program A, Program B veya Program C’yi takip etmek \u00fczere rastgele 30 ki\u015fiyi atad\u0131\u011f\u0131m\u0131z bir deneye kat\u0131lmak \u00fczere 90 ki\u015fiyi i\u015fe al\u0131yoruz.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, bu tek y\u00f6nl\u00fc ANOVA’y\u0131 ger\u00e7ekle\u015ftirmek i\u00e7in R’de aov()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n Model sonu\u00e7lar\u0131ndan program\u0131n p de\u011ferinin (0,0000000000755) 0,05’ten k\u00fc\u00e7\u00fck oldu\u011funu g\u00f6rebiliyoruz, bu da \u00fc\u00e7 program aras\u0131nda ortalama kilo kayb\u0131 a\u00e7\u0131s\u0131ndan istatistiksel olarak anlaml\u0131 bir fark oldu\u011fu anlam\u0131na geliyor.<\/span><\/p>\n Belirli bir \u00fcniversitedeki \u00f6\u011frencilerin s\u0131nav puanlar\u0131n\u0131<\/strong> tahmin etmek i\u00e7in \u00e7al\u0131\u015f\u0131lan saat say\u0131s\u0131n\u0131<\/strong> kullanmak istedi\u011fimizi varsayal\u0131m. A\u015fa\u011f\u0131daki iki regresyon modelini uyarlamaya karar verebiliriz:<\/span><\/p>\n Tam model:<\/strong> puan = \u03b2 0<\/sub> + B 1<\/sub> (saat) + B 2<\/sub> (saat) 2<\/sup><\/span><\/p>\n \u0130ndirgenmi\u015f model:<\/strong> puan = \u03b2 0<\/sub> + B 1<\/sub> (saat)<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, tam modelin azalt\u0131lm\u0131\u015f modelden \u00f6nemli \u00f6l\u00e7\u00fcde daha iyi bir uyum sa\u011flay\u0131p sa\u011flamad\u0131\u011f\u0131n\u0131 belirlemek amac\u0131yla uyum eksikli\u011fi testi ger\u00e7ekle\u015ftirmek i\u00e7in R’deki anova()<\/strong> i\u015flevinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n \u00c7\u0131kt\u0131 tablosundaki p de\u011feri (0,002144) 0,05’ten k\u00fc\u00e7\u00fck oldu\u011fundan, testin s\u0131f\u0131r hipotezini reddedebilir ve tam modelin indirgenmi\u015f modelden istatistiksel olarak anlaml\u0131 derecede daha iyi bir uyum sa\u011flad\u0131\u011f\u0131 sonucuna varabiliriz.<\/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 tek y\u00f6nl\u00fc ANOVA nas\u0131l ger\u00e7ekle\u015ftirilir<\/a> R’deki aov() ve anova() i\u015flevleri benzer g\u00f6r\u00fcnse de asl\u0131nda bunlar\u0131 iki farkl\u0131 senaryoda kullan\u0131yoruz. Bir ANOVA modeline s\u0131\u011fd\u0131rmak ve sonu\u00e7lar\u0131 bir ANOVA \u00f6zet tablosunda g\u00f6r\u00fcnt\u00fclemek istedi\u011fimizde aov() kullan\u0131r\u0131z. Belirli bir katsay\u0131lar dizisine sahip bir regresyon modelinin, yaln\u0131zca bir katsay\u0131lar alt k\u00fcmesine sahip bir modele g\u00f6re \u00f6nemli \u00f6l\u00e7\u00fcde daha iyi bir uyum sa\u011flay\u0131p sa\u011flamad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in […]<\/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-3451","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek 1: R’de aov() nas\u0131l kullan\u0131l\u0131r?<\/strong><\/span><\/h2>\n
#make this example reproducible\n<\/span>set. seeds<\/span> (0)\n\n#create data frame\n<\/span>df <- 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#fit one-way anova using aov()\n<\/span>fit <- aov(weight_loss ~ program, data=df)\n\n#view results\n<\/span>summary(fit)\n\n Df Sum Sq Mean Sq F value Pr(>F) \nprogram 2 98.93 49.46 30.83 7.55e-11 ***\nResiduals 87 139.57 1.60 \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n<\/strong><\/pre>\n \u00d6rnek 2: R’de anova() nas\u0131l kullan\u0131l\u0131r?<\/strong><\/span><\/h2>\n
#make this example reproducible\nset. seeds<\/span> (1)\n\n#create dataset\n<\/span>df <- data.frame(hours = runif(50, 5, 15), score=50)\ndf$score = df$score + df$hours^3\/150 + df$hours*runif(50, 1, 2)\n\n#view head of data\n<\/span>head(df)\n\n hours score\n1 7.655087 64.30191\n2 8.721239 70.65430\n3 10.728534 73.66114\n4 14.082078 86.14630\n5 7.016819 59.81595\n6 13.983897 83.60510\n\n#fit full model\n<\/span>full <- lm(score ~ poly(hours,2), data=df)\n\n#fit reduced model\n<\/span>reduced <- lm(score ~ hours, data=df)\n\n#perform lack of fit test using anova()\n<\/span>anova(full, reduced)\n\nAnalysis of Variance Table\n\nModel 1: score ~ poly(hours, 2)\nModel 2: score ~ hours\n Res.Df RSS Df Sum of Sq F Pr(>F) \n1 47 368.48 \n2 48 451.22 -1 -82.744 10.554 0.002144 **\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/span><\/span><\/strong><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
R’de iki y\u00f6nl\u00fc ANOVA nas\u0131l ger\u00e7ekle\u015ftirilir<\/a>
R’de tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"