{"id":1615,"date":"2023-07-25T15:42:09","date_gmt":"2023-07-25T15:42:09","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%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":"2023-07-25T15:42:09","modified_gmt":"2023-07-25T15:42:09","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%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\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%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":"Python\uc758 welch\uc758 anova(\ub2e8\uacc4\ubcc4)"},"content":{"rendered":"

<\/p>\n

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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 Python\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

 A = [64, 66, 68, 75, 78, 94, 98, 79, 71, 80]\nB = [91, 92, 93, 90, 97, 94, 82, 88, 95, 96]\nC = [79, 78, 88, 94, 92, 85, 83, 85, 82, 81]\n<\/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
 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec Python\uc5d0\uc11c Bartlett \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 import<\/span> scipy. stats<\/span> as<\/span> stats\n\n#perform Bartlett's test \n<\/span>stats. bartlett<\/span> (A, B, C)\n\nBartlettResult(statistic=9.039674395, pvalue=0.010890796567)\n<\/strong><\/span><\/pre>\n
 Bartlett \uac80\uc815\uc758 p-\uac12( .01089<\/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
 Python\uc5d0\uc11c Welch\uc758 ANOVA\ub97c \uc218\ud589\ud558\ub824\uba74 Penguin \ud328\ud0a4\uc9c0\uc758 welch_anova()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uba3c\uc800 Penguin\uc744 \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n
 pip install<\/span> Penguin<\/span>\n<\/strong><\/pre>\n
 \uadf8\ub7f0 \ub2e4\uc74c \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec Welch\uc758 ANOVA\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 import penguin<\/span> as pg<\/span>\nimport<\/span> pandas as<\/span> pd\nimport<\/span> numpy as<\/span> np\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' score<\/span> ': [64, 66, 68, 75, 78, 94, 98, 79, 71, 80,\n                             91, 92, 93, 90, 97, 94, 82, 88, 95, 96,\n                             79, 78, 88, 94, 92, 85, 83, 85, 82, 81],\n                   ' group<\/span> ': np. repeat<\/span> (['a', 'b', 'c'], repeats<\/span> = 10<\/span> )}) \n\n#perform Welch's ANOVA\n<\/span>pg. welch_anova<\/span> (dv=' score<\/span> ', between=' group<\/span> ', data=df)\n\n        Source ddof1 ddof2 F p-unc np2\n0 group 2 16.651295 9.717185 0.001598 0.399286\n<\/strong><\/pre>\n
 ANOVA \ud14c\uc774\ube14\uc758 \uc804\uccb4 p-\uac12( 0.001598<\/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 Games-Howell \uc0ac\ud6c4 \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\uc5ec \uc815\ud655\ud788 \uc5b4\ub5a4 \uadf8\ub8f9\uc758 \ud3c9\uade0\uc774 \ub2e4\ub978\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 pg. pairwise_gameshowell<\/span> (dv=' score<\/span> ', between=' group<\/span> ', data=df)\n\n\n        A B mean(A) mean(B) diff se T df pval\t\n0 a b 77.3 91.8 -14.5 3.843754 -3.772354 11.6767 0.0072\n1 a c 77.3 84.7 -7.4 3.952777 -1.872102 12.7528 0.1864\n2 b c 91.8 84.7 7.1 2.179959 3.256942 17.4419 0.0119\n<\/strong><\/pre>\n
 p-\uac12\uc744 \ubcf4\uba74 \uadf8\ub8f9 a<\/strong> \uc640 b<\/strong> \uc0ac\uc774\uc758 \ud3c9\uade0 \ucc28\uc774\uac00 \uc720\uc758\ud558\uac8c \ub2e4\ub974\uba70 \uadf8\ub8f9 b<\/strong> \uc640 c<\/strong> \uc0ac\uc774\uc758 \ud3c9\uade0 \ucc28\uc774\ub3c4 \uc720\uc758\ud558\uac8c \ub2e4\ub974\ub2e4\ub294 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 Python\uc5d0\uc11c \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 Python\uc5d0\uc11c \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 Python\uc5d0\uc11c \ubc18\ubcf5 \uce21\uc815 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
Welch\uc758 \ubd84\uc0b0 \ubd84\uc11d\uc740 \ub4f1\ubd84\uc0b0 \uac00\uc815\uc774 \ucda9\uc871\ub418\uc9c0 \uc54a\ub294 \uacbd\uc6b0 \uc77c\ubc18\uc801\uc778 \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc5d0 \ub300\ud55c \ub300\uc548\uc785\ub2c8\ub2e4. \ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc5d0\uc11c\ub294 Python\uc5d0\uc11c Welch\uc758 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. 1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131 \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 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1615","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nPython\uc758 Welch\uc758 ANOVA(\ub2e8\uacc4\ubcc4)<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \ub2e8\uacc4\ubcc4 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec Python\uc5d0\uc11c Welch\uc758 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1174-\u110b\u1170\u11af\u110e\u1175\u1109\u1173-\u110b\u1161\u1102\u1169\u1107\u1161\/\" \/>\n<meta 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