{"id":852,"date":"2023-07-28T13:03:16","date_gmt":"2023-07-28T13:03:16","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-anova-%e1%84%8b%e1%85%a3%e1%86%bc%e1%84%87%e1%85%a1%e1%86%bc%e1%84%92%e1%85%a3%e1%86%bc\/"},"modified":"2023-07-28T13:03:16","modified_gmt":"2023-07-28T13:03:16","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab-anova-%e1%84%8b%e1%85%a3%e1%86%bc%e1%84%87%e1%85%a1%e1%86%bc%e1%84%92%e1%85%a3%e1%86%bc","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-anova-%e1%84%8b%e1%85%a3%e1%86%bc%e1%84%87%e1%85%a1%e1%86%bc%e1%84%92%e1%85%a3%e1%86%bc\/","title":{"rendered":"Python\uc5d0\uc11c \uc591\ubc29\ud5a5 anova\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ko\/\u110b\u1163\u11bc\u1107\u1161\u11bc\u1112\u1163\u11bc-\u110b\u1161\u1102\u1169\u1107\u1161\/\" target=\"_blank\" rel=\"noopener\">\uc591\ubc29\ud5a5 ANOVA\ub294 \ub450 \uc694\uc778\uc73c\ub85c \ubd84\ud560<\/a> \ub41c 3\uac1c \uc774\uc0c1\uc758 \ub3c5\ub9bd \uadf8\ub8f9 \ud3c9\uade0 \uac04\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\uac00 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc591\ubc29\ud5a5 \ubd84\uc0b0 \ubd84\uc11d\uc758 \ubaa9\uc801\uc740 \ub450 \uc694\uc778\uc774 \ubc18\uc751 \ubcc0\uc218\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5\uc744 \ud655\uc778\ud558\uace0 \ub450 \uc694\uc778 \uc0ac\uc774\uc5d0 \ubc18\uc751 \ubcc0\uc218\uc5d0 \ub300\ud55c \uc0c1\ud638 \uc791\uc6a9\uc774 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\uc608: Python\uc758 \uc591\ubc29\ud5a5 ANOVA<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ud55c \uc2dd\ubb3c\ud559\uc790\ub294 \ud587\ube5b \ub178\ucd9c\uacfc \ubb3c\uc8fc\uae30 \ube48\ub3c4\uac00 \uc2dd\ubb3c \uc131\uc7a5\uc5d0 \uc601\ud5a5\uc744 \ubbf8\uce58\ub294\uc9c0 \uc54c\uace0 \uc2f6\uc5b4\ud569\ub2c8\ub2e4. \uadf8\ub140\ub294 30\uac1c\uc758 \uc528\uc557\uc744 \uc2ec\uace0 \ud587\ube5b \ub178\ucd9c\uacfc \ubb3c \uc8fc\uae30 \ub4f1 \ub2e4\uc591\ud55c \uc870\uac74\uc5d0\uc11c \ub450 \ub2ec \ub3d9\uc548 \uc528\uc557\uc774 \uc790\ub77c\uac8c \ud569\ub2c8\ub2e4. \ub450 \ub2ec \ud6c4\uc5d0 \uadf8\ub140\ub294 \uac01 \uc2dd\ubb3c\uc758 \ub192\uc774\ub97c \uc778\uce58 \ub2e8\uc704\ub85c \uae30\ub85d\ud588\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ub2e8\uacc4\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\uc5ec \ubb3c \uc8fc\ub294 \ube48\ub3c4\uc640 \ud0dc\uc591 \ub178\ucd9c\uc774 \uc2dd\ubb3c \uc131\uc7a5\uc5d0 \uc911\uc694\ud55c \uc601\ud5a5\uc744 \ubbf8\uce58\ub294\uc9c0 \ud655\uc778\ud558\uace0 \ubb3c \ube48\ub3c4\uc640 \ud0dc\uc591 \ub178\ucd9c \uc0ac\uc774\uc5d0 \uc0c1\ud638 \uc791\uc6a9 \ud6a8\uacfc\uac00 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud569\ub2c8\ub2e4. \ubb3c\uc8fc\uae30 \ubc0f \ud587\ube5b \ub178\ucd9c.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1\ub2e8\uacc4: \ub370\uc774\ud130\ub97c \uc785\ub825\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uba3c\uc800 \ub2e4\uc74c \uc138 \uac00\uc9c0 \ubcc0\uc218\ub97c \ud3ec\ud568\ud558\ub294 pandas DataFrame\uc744 \ub9cc\ub4ed\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\ubb3c:<\/strong> \uac01 \uc2dd\ubb3c\uc5d0 \ubb3c\uc744 \uc8fc\ub294 \ube48\ub3c4: \ub9e4\uc77c \ub610\ub294 \ub9e4\uc8fc<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ud0dc\uc591:<\/strong> \uac01 \uc2dd\ubb3c\uc774 \ubc1b\ub294 \ud0dc\uc591 \ub178\ucd9c\uc758 \uc591: \ub0ae\uc74c, \uc911\uac04, \ub192\uc74c<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ub192\uc774:<\/strong> 2\uac1c\uc6d4 \ud6c4 \uac01 \uc2dd\ubb3c\uc758 \ub192\uc774(\uc778\uce58)<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n<span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data<\/span>\ndf = pd.DataFrame({'water': np.repeat(['daily', 'weekly'], 15),\n                   'sun': np.tile(np.repeat(['low', 'med', 'high'], 5), 2),\n                   'height': [6, 6, 6, 5, 6, 5, 5, 6, 4, 5,\n                              6, 6, 7, 8, 7, 3, 4, 4, 4, 5,\n                              4, 4, 4, 4, 4, 5, 6, 6, 7, 8]})\n\n<span style=\"color: #008080;\">#view first ten rows of data<\/span> \ndf[:10]\n\n\twater sun height\n0 daily low 6\n1 daily low 6\n2 daily low 6\n3 daily low 5\n4 daily low 6\n5 daily med 5\n6 daily med 5\n7 daily med 6\n8 daily med 4\n9 daily med 5\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>2\ub2e8\uacc4: \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c statsmodels \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758 <a href=\"https:\/\/www.statsmodels.org\/dev\/generated\/statsmodels.stats.anova.anova_lm.html\" target=\"_blank\" rel=\"noopener\">anova_lm() \ud568\uc218\ub97c<\/a> \uc0ac\uc6a9\ud558\uc5ec \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> statsmodels.api <span style=\"color: #107d3f;\">as<\/span> sm\n<span style=\"color: #107d3f;\">from<\/span> statsmodels.formula.api <span style=\"color: #107d3f;\">import<\/span> ols\n\n<span style=\"color: #008080;\">#perform two-way ANOVA<\/span>\nmodel = ols('height ~ C(water) + C(sun) + C(water):C(sun)', data=df).fit()\nsm.stats.anova_lm(model, typ=2)\n\n\t           sum_sq df F PR(&gt;F)\nC(water) 8.533333 1.0 16.0000 0.000527\nC(sun) 24.866667 2.0 23.3125 0.000002\nC(water):C(sun) 2.466667 2.0 2.3125 0.120667\nResidual 12.800000 24.0 NaN NaN\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>3\ub2e8\uacc4: \uacb0\uacfc\ub97c \ud574\uc11d\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\ud45c\uc758 \uac01 \uc694\uc778\uc5d0 \ub300\ud574 \ub2e4\uc74c\uacfc \uac19\uc740 p-\uac12\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\ubb3c:<\/strong> p-\uac12 = 0.000527<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ud0dc\uc591:<\/strong> p-\uac12 = 0.0000002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ubb3c*\ud0dc\uc591:<\/strong> p-\uac12 = 0.120667<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\ubb3c\uacfc \ud0dc\uc591\uc5d0 \ub300\ud55c p-\uac12\uc774 \ubaa8\ub450 0.05 \ubbf8\ub9cc\uc774\ubbc0\ub85c \uc774\ub294 \ub450 \uc694\uc18c \ubaa8\ub450 \uc2dd\ubb3c \ud0a4\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \uc601\ud5a5\uc744 \ubbf8\uce5c\ub2e4\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub9ac\uace0 \uc0c1\ud638\uc791\uc6a9 \ud6a8\uacfc\uc5d0 \ub300\ud55c p-\uac12(0.120667)\uc774 0.05 \uc774\uc0c1\uc774\ubbc0\ub85c \uc774\ub294 \ud0dc\uc591 \ub178\ucd9c\uacfc \ubb3c\uc8fc\uae30 \ube48\ub3c4 \uc0ac\uc774\uc5d0 \uc720\uc758\ubbf8\ud55c \uc0c1\ud638\uc791\uc6a9 \ud6a8\uacfc\uac00 \uc5c6\uc74c\uc744 \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0:<\/strong> ANOVA \uacb0\uacfc\uc5d0 \ub530\ub974\uba74 \ubb3c \uc8fc\ub294 \ube48\ub3c4\uc640 \ud587\ube5b \ub178\ucd9c\uc774 \uc2dd\ubb3c \ub192\uc774\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \uc601\ud5a5\uc744 \ubbf8\uce5c\ub2e4\ub294 \uc0ac\uc2e4\uc774 \ubc1d\ud600\uc84c\uc9c0\ub9cc, \ubb3c\uacfc \ud587\ube5b \uc218\uc900\uc774 \uc2dd\ubb3c \ub192\uc774\uc5d0 \uc5b4\ub5bb\uac8c \uc601\ud5a5\uc744 \ubbf8\uce58\ub294\uc9c0 \uc815\ud655\ud558\uac8c \ud655\uc778\ud558\ub824\uba74 <a href=\"https:\/\/statorials.org\/ko\/\u1109\u1161\u1112\u116e-anova-\u1110\u1166\u1109\u1173\u1110\u1173\/\" target=\"_blank\" rel=\"noopener\">\uc0ac\ud6c4 \ud14c\uc2a4\ud2b8\ub97c<\/a> \uc218\ud589\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1103\u1161\u11ab\u1107\u1161\u11bc\u1112\u1163\u11bc-\u110b\u1161\u1102\u1169\u1107\u1161-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/3\u1107\u1161\u11bc\u1112\u1163\u11bc-\u110b\u1161\u1102\u1169\u1107\u1161-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c 3\uc6d0 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc591\ubc29\ud5a5 ANOVA\ub294 \ub450 \uc694\uc778\uc73c\ub85c \ubd84\ud560 \ub41c 3\uac1c \uc774\uc0c1\uc758 \ub3c5\ub9bd \uadf8\ub8f9 \ud3c9\uade0 \uac04\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\uac00 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc591\ubc29\ud5a5 \ubd84\uc0b0 \ubd84\uc11d\uc758 \ubaa9\uc801\uc740 \ub450 \uc694\uc778\uc774 \ubc18\uc751 \ubcc0\uc218\uc5d0 \ubbf8\uce58\ub294 \uc601\ud5a5\uc744 \ud655\uc778\ud558\uace0 \ub450 \uc694\uc778 \uc0ac\uc774\uc5d0 \ubc18\uc751 \ubcc0\uc218\uc5d0 \ub300\ud55c \uc0c1\ud638 \uc791\uc6a9\uc774 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. \uc608: Python\uc758 \uc591\ubc29\ud5a5 ANOVA [&hellip;]<\/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-852","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python\uc5d0\uc11c \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95 - Statorials<\/title>\n<meta name=\"description\" content=\"Python\uc5d0\uc11c \uc591\ubc29\ud5a5 ANOVA\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \uac04\ub2e8\ud55c \uc124\uba85\uc785\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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