{"id":1614,"date":"2023-07-25T15:47:14","date_gmt":"2023-07-25T15:47:14","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%b0%e1%86%af%e1%84%8e%e1%85%b5%e1%84%89%e1%85%b3-%e1%84%8b%e1%85%a1%e1%84%82%e1%85%a9%e1%84%87%e1%85%a1\/"},"modified":"2023-07-25T15:47:14","modified_gmt":"2023-07-25T15:47:14","slug":"r%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%b0%e1%86%af%e1%84%8e%e1%85%b5%e1%84%89%e1%85%b3-%e1%84%8b%e1%85%a1%e1%84%82%e1%85%a9%e1%84%87%e1%85%a1","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8b%e1%85%b0%e1%86%af%e1%84%8e%e1%85%b5%e1%84%89%e1%85%b3-%e1%84%8b%e1%85%a1%e1%84%82%e1%85%a9%e1%84%87%e1%85%a1\/","title":{"rendered":"R\uc5d0\uc11c welch\uc758 anova\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95(\ub2e8\uacc4\ubcc4)"},"content":{"rendered":"

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Welch\uc758 \ubd84\uc0b0 \ubd84\uc11d\uc740<\/strong> \ub4f1\ubd84\uc0b0 \uac00\uc815\uc774<\/a> \ucda9\uc871\ub418\uc9c0 \uc54a\ub294 \uacbd\uc6b0 \uc77c\ubc18\uc801\uc778 \uc77c\uc6d0 \ubd84\uc0b0<\/a> \ubd84\uc11d\uc5d0 \ub300\ud55c \ub300\uc548\uc785\ub2c8\ub2e4.<\/span><\/p>\n

\ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc5d0\uc11c\ub294 R\uc5d0\uc11c Welch\uc758 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n

1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131<\/strong><\/span><\/h3>\n

\uc138 \uac00\uc9c0 \ud559\uc2b5 \ubc29\ubc95\uc774 \uc11c\ub85c \ub2e4\ub978 \uc2dc\ud5d8 \uacb0\uacfc\ub97c \uac00\uc838\uc624\ub294\uc9c0 \ud655\uc778\ud558\uae30 \uc704\ud574 \uad50\uc218\ub294 \ubb34\uc791\uc704\ub85c 10\uba85\uc758 \ud559\uc0dd\uc5d0\uac8c \uac01 \uae30\uc220(\uae30\uc220 A, B \ub610\ub294 C)\uc744 \uc77c\uc8fc\uc77c \ub3d9\uc548 \uc0ac\uc6a9\ud558\ub3c4\ub85d \ud560\ub2f9\ud55c \ub2e4\uc74c \uac01 \ud559\uc0dd\uc5d0\uac8c \ub3d9\uc77c\ud55c \ub09c\uc774\ub3c4\uc758 \ud14c\uc2a4\ud2b8\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n

30\uba85\uc758 \ud559\uc0dd\uc758 \uc2dc\ud5d8 \uacb0\uacfc\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 #create data frame<\/span>\ndf <-data. frame<\/span> (group = rep<\/span> (c(' A<\/span> ', ' B<\/span> ', ' C<\/span> '), each<\/span> =10),\n                score = c(64, 66, 68, 75, 78, 94, 98, 79, 71, 80,\n                          91, 92, 93, 85, 87, 84, 82, 88, 95, 96,\n                          79, 78, 88, 94, 92, 85, 83, 85, 82, 81))\n\n#view first six rows of data frame\n<\/span>head(df)\n\n   group score\n1 to 64\n2 to 66\n3 to 68\n4 to 75\n5 to 78\n6 to 94<\/strong><\/pre>\n
 2\ub2e8\uacc4: \ub4f1\ucc28 \ud14c\uc2a4\ud2b8<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c\uc73c\ub85c Bartlett \ud14c\uc2a4\ud2b8\ub97c<\/a> \uc218\ud589\ud558\uc5ec \uac01 \uadf8\ub8f9 \uac04\uc758 \ubd84\uc0b0\uc774 \ub3d9\uc77c\ud55c\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uac80\uc815 \ud1b5\uacc4\ub7c9\uc758 p-\uac12\uc774<\/a> \ud2b9\uc815 \uc720\uc758 \uc218\uc900(\uc608: \u03b1 = 0.05)\ubcf4\ub2e4 \ub0ae\uc73c\uba74 \uadc0\ubb34 \uac00\uc124\uc744 \uae30\uac01\ud558\uace0 \ubaa8\ub4e0 \uadf8\ub8f9\uc758 \ubd84\uc0b0\uc774 \ub3d9\uc77c\ud558\uc9c0 \uc54a\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 Bartlett \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 \uae30\ubcf8 R\uc5d0\uc11c bartlett.test<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 bartlett.test(\uacf5\uc2dd, \ub370\uc774\ud130)<\/strong><\/span><\/p>\n
 \uc608\uc81c\uc5d0\uc11c \uc774 \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #perform Bartlett's test\n<\/span>bartlett. test<\/span> (score ~ group, data = df)\n\n\tBartlett test of homogeneity of variances\n\ndata: score by group\nBartlett's K-squared = 8.1066, df = 2, p-value = 0.01737\n<\/strong><\/pre>\n
 Bartlett \uac80\uc815\uc758 p-\uac12( .01737<\/strong> )\uc740 \u03b1 = .05\ubcf4\ub2e4 \uc791\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uac01 \uadf8\ub8f9\uc774 \ub3d9\uc77c\ud55c \ubd84\uc0b0\uc744 \uac16\ub294\ub2e4\ub294 \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud560 \uc218 \uc788\uc74c\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ub530\ub77c\uc11c \ub4f1\ubd84\uc0b0 \uac00\uc815\uc774 \uc704\ubc18\ub418\uba70 Welch\uc758 ANOVA\ub97c \uc9c4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 3\ub2e8\uacc4: Welch\uc758 \ubd84\uc0b0 \ubd84\uc11d \uc218\ud589<\/strong><\/span><\/h3>\n
 R\uc5d0\uc11c Welch\uc758 ANOVA\ub97c \uc218\ud589\ud558\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 R \uae30\ubcf8 oneway.test()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #perform Welch's ANOVA\n<\/span>oneway. test<\/span> (score ~ group, data = df, var. equal<\/span> = FALSE<\/span> )\n\n\tOne-way analysis of means (not assuming equal variances)\n\ndata: score and group\nF = 5.3492, num df = 2.00, denom df = 16.83, p-value = 0.01591\n<\/strong><\/pre>\n
 ANOVA \ud14c\uc774\ube14\uc758 \uc804\uccb4 p-\uac12( 0.01591<\/strong> )\uc740 \u03b1 = 0.05\ubcf4\ub2e4 \uc791\uc2b5\ub2c8\ub2e4. \uc774\ub294 \uc138 \uac00\uc9c0 \ud559\uc2b5 \uae30\ubc95 \uac04\uc5d0 \uc2dc\ud5d8 \uacb0\uacfc\uac00 \ub3d9\uc77c\ud558\ub2e4\ub294 \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud560 \uc218 \uc788\uc74c\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \uadf8\ub7f0 \ub2e4\uc74c \uc0ac\ud6c4 \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\uc5ec \uc5b4\ub5a4 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub2e4\ub978\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. R\uc5d0\uc11c \ub2e4\uc591\ud55c \uc0ac\ud6c4 \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\ub824\uba74 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc744 \ucc38\uc870\ud558\uc2ed\uc2dc\uc624.<\/span><\/p>\n