{"id":854,"date":"2023-07-28T12:45:51","date_gmt":"2023-07-28T12:45:51","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%b0%d0%bd%d0%ba%d0%be%d0%b2%d0%b0-%d0%bf%d1%96%d1%82%d0%be%d0%bd\/"},"modified":"2023-07-28T12:45:51","modified_gmt":"2023-07-28T12:45:51","slug":"%d0%b0%d0%bd%d0%ba%d0%be%d0%b2%d0%b0-%d0%bf%d1%96%d1%82%d0%be%d0%bd","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%b0%d0%bd%d0%ba%d0%be%d0%b2%d0%b0-%d0%bf%d1%96%d1%82%d0%be%d0%bd\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ancova \u0432 python"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">ANCOVA<\/span> <span style=\"color: #000000;\">(\u00ab\u043a\u043e\u0432\u0430\u0440\u0456\u0430\u0446\u0456\u0439\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437\u00bb) \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f, \u0449\u043e\u0431 \u0432\u0438\u0437\u043d\u0430\u0447\u0438\u0442\u0438, \u0447\u0438 \u0456\u0441\u043d\u0443\u0454 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u043e \u0437\u043d\u0430\u0447\u0443\u0449\u0430 \u0440\u0456\u0437\u043d\u0438\u0446\u044f \u043c\u0456\u0436 \u0441\u0435\u0440\u0435\u0434\u043d\u0456\u043c\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f\u043c\u0438 \u0442\u0440\u044c\u043e\u0445 \u0430\u0431\u043e \u0431\u0456\u043b\u044c\u0448\u0435 \u043d\u0435\u0437\u0430\u043b\u0435\u0436\u043d\u0438\u0445 \u0433\u0440\u0443\u043f, \u043f\u0456\u0441\u043b\u044f \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044e \u043e\u0434\u043d\u0456\u0454\u0457 \u0430\u0431\u043e \u043a\u0456\u043b\u044c\u043a\u043e\u0445<a href=\"https:\/\/statorials.org\/uk\/\u043a\u043e\u0432\u0430\u0440\u0456\u0430\u043d\u0442-2\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u043a\u043e\u0432\u0430\u0440\u0456\u0430\u0442<\/a><\/span> <a href=\"https:\/\/statorials.org\/uk\/\u0430\u043d\u043a\u043e\u0432\/\" target=\"_blank\" rel=\"noopener noreferrer\">.<\/a><\/p>\n<p> <span style=\"color: #000000;\">\u0426\u0435\u0439 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434: ANCOVA \u0432 Python<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0412\u0438\u043a\u043b\u0430\u0434\u0430\u0447 \u0445\u043e\u0447\u0435 \u0437\u043d\u0430\u0442\u0438, \u0447\u0438 \u0442\u0440\u0438 \u0440\u0456\u0437\u043d\u0456 \u043c\u0435\u0442\u043e\u0434\u0438 \u043d\u0430\u0432\u0447\u0430\u043d\u043d\u044f \u0432\u043f\u043b\u0438\u0432\u0430\u044e\u0442\u044c \u043d\u0430 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 \u0456\u0441\u043f\u0438\u0442\u0443, \u0430\u043b\u0435 \u0432\u0456\u043d \u0445\u043e\u0447\u0435 \u0432\u0437\u044f\u0442\u0438 \u0434\u043e \u0443\u0432\u0430\u0433\u0438 \u043f\u043e\u0442\u043e\u0447\u043d\u0443 \u043e\u0446\u0456\u043d\u043a\u0443, \u044f\u043a\u0443 \u0441\u0442\u0443\u0434\u0435\u043d\u0442 \u0443\u0436\u0435 \u043c\u0430\u0454 \u0432 \u043a\u043b\u0430\u0441\u0456.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412\u0456\u043d \u0432\u0438\u043a\u043e\u043d\u0430\u0454 ANCOVA \u0437 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f\u043c \u0442\u0430\u043a\u0438\u0445 \u0437\u043c\u0456\u043d\u043d\u0438\u0445:<\/span><\/p>\n<ul data-slot-rendered-dynamic=\"true\">\n<li> <span style=\"color: #000000;\"><strong>\u0424\u0430\u043a\u0442\u043e\u0440\u043d\u0430 \u0437\u043c\u0456\u043d\u043d\u0430:<\/strong> \u0442\u0435\u0445\u043d\u0456\u0447\u043d\u0435 \u0434\u043e\u0441\u043b\u0456\u0434\u0436\u0435\u043d\u043d\u044f<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u041a\u043e\u0432\u0430\u0440\u0456\u0430\u043d\u0442:<\/strong> \u043f\u043e\u0442\u043e\u0447\u043d\u0438\u0439 \u0431\u0430\u043b<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u0417\u043c\u0456\u043d\u043d\u0430 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456:<\/strong> \u0456\u0441\u043f\u0438\u0442\u043e\u0432\u0438\u0439 \u0431\u0430\u043b<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0412\u0438\u043a\u043e\u043d\u0430\u0439\u0442\u0435 \u0442\u0430\u043a\u0456 \u0434\u0456\u0457, \u0449\u043e\u0431 \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0434\u043b\u044f \u0446\u044c\u043e\u0433\u043e \u043d\u0430\u0431\u043e\u0440\u0443 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 1: \u0412\u0432\u0435\u0434\u0456\u0442\u044c \u0434\u0430\u043d\u0456.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0421\u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u043c\u0438 \u0441\u0442\u0432\u043e\u0440\u0438\u043c\u043e pandas DataFrame \u0434\u043b\u044f \u0437\u0431\u0435\u0440\u0456\u0433\u0430\u043d\u043d\u044f \u043d\u0430\u0448\u0438\u0445 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\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({'technique': np.repeat(['A', 'B', 'C'], 5),\n                   'current_grade': [67, 88, 75, 77, 85,\n                                     92, 69, 77, 74, 88, \n                                     96, 91, 88, 82, 80],\n                   'exam_score': [77, 89, 72, 74, 69,\n                                  78, 88, 93, 94, 90,\n                                  85, 81, 83, 88, 79]})\n<span style=\"color: #008080;\">#view data<\/span> \ndf\n\n   technical current_grade exam_score\n0 A 67 77\n1 A 88 89\n2 A 75 72\n3 A 77 74\n4 A 85 69\n5 B 92 78\n6 B 69 88\n7 B 77 93\n8 B 74 94\n9 B 88 90\n10 C 96 85\n11 C 91 81\n12 C 88 83\n13 C 82 88\n14 C 80 79\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 2: \u0412\u0438\u043a\u043e\u043d\u0430\u0439\u0442\u0435 ANCOVA.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0414\u0430\u043b\u0456 \u043c\u0438 \u0432\u0438\u043a\u043e\u043d\u0430\u0454\u043c\u043e ANCOVA \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e <a href=\"https:\/\/pingouin-stats.org\/generated\/pingouin.ancova.html\" target=\"_blank\" rel=\"noopener noreferrer\">\u0444\u0443\u043d\u043a\u0446\u0456\u0457 ancova()<\/a> \u0437 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u043a\u0438 penguin:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\"><span style=\"color: #000000;\">pip<\/span> install <span style=\"color: #000000;\">penguin<\/span> \nfrom<\/span> penguin <span style=\"color: #107d3f;\">import<\/span> ancova\n\n<span style=\"color: #008080;\">#perform ANCOVA<\/span>\nancova(data= <span style=\"color: #008000;\">df<\/span> , dv=' <span style=\"color: #008000;\">exam_score<\/span> ', covar=' <span style=\"color: #008000;\">current_grade<\/span> ', between=' <span style=\"color: #008000;\">technique<\/span> ')\n\n\n        Source SS DF F p-unc np2\n0 technical 390.575130 2 4.80997 0.03155 0.46653\n1 current_grade 4.193886 1 0.10329 0.75393 0.00930\n2 Residual 446.606114 11 NaN NaN NaN\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 3: \u0406\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0456\u044f \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0456\u0432.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0417 \u0442\u0430\u0431\u043b\u0438\u0446\u0456 ANCOVA \u043c\u0438 \u0431\u0430\u0447\u0438\u043c\u043e, \u0449\u043e p-value (p-unc = \u00abuncorrected p-value\u00bb) \u0434\u043b\u044f \u043c\u0435\u0442\u043e\u0434\u0438\u043a\u0438 \u0434\u043e\u0441\u043b\u0456\u0434\u0436\u0435\u043d\u043d\u044f \u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u044c <strong>0,03155<\/strong> . \u041e\u0441\u043a\u0456\u043b\u044c\u043a\u0438 \u0446\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043c\u0435\u043d\u0448\u0435 0,05, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0456\u0434\u0445\u0438\u043b\u0438\u0442\u0438 \u043d\u0443\u043b\u044c\u043e\u0432\u0443 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0443 \u043f\u0440\u043e \u0442\u0435, \u0449\u043e \u043a\u043e\u0436\u0435\u043d \u0456\u0437 \u043c\u0435\u0442\u043e\u0434\u0456\u0432 \u043d\u0430\u0432\u0447\u0430\u043d\u043d\u044f \u043f\u0440\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u044c \u0434\u043e \u043e\u0434\u043d\u0430\u043a\u043e\u0432\u043e\u0457 \u0441\u0435\u0440\u0435\u0434\u043d\u044c\u043e\u0457 \u043e\u0446\u0456\u043d\u043a\u0438 \u0456\u0441\u043f\u0438\u0442\u0443, <em>\u043d\u0430\u0432\u0456\u0442\u044c \u044f\u043a\u0449\u043e \u0432\u0440\u0430\u0445\u0443\u0432\u0430\u0442\u0438 \u043f\u043e\u0442\u043e\u0447\u043d\u0443 \u043e\u0446\u0456\u043d\u043a\u0443 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u0430 \u0432 \u043a\u043b\u0430\u0441\u0456<\/em> .<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>ANCOVA (\u00ab\u043a\u043e\u0432\u0430\u0440\u0456\u0430\u0446\u0456\u0439\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437\u00bb) \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f, \u0449\u043e\u0431 \u0432\u0438\u0437\u043d\u0430\u0447\u0438\u0442\u0438, \u0447\u0438 \u0456\u0441\u043d\u0443\u0454 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u043e \u0437\u043d\u0430\u0447\u0443\u0449\u0430 \u0440\u0456\u0437\u043d\u0438\u0446\u044f \u043c\u0456\u0436 \u0441\u0435\u0440\u0435\u0434\u043d\u0456\u043c\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f\u043c\u0438 \u0442\u0440\u044c\u043e\u0445 \u0430\u0431\u043e \u0431\u0456\u043b\u044c\u0448\u0435 \u043d\u0435\u0437\u0430\u043b\u0435\u0436\u043d\u0438\u0445 \u0433\u0440\u0443\u043f, \u043f\u0456\u0441\u043b\u044f \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u044e \u043e\u0434\u043d\u0456\u0454\u0457 \u0430\u0431\u043e \u043a\u0456\u043b\u044c\u043a\u043e\u0445\u043a\u043e\u0432\u0430\u0440\u0456\u0430\u0442 . \u0426\u0435\u0439 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python. \u041f\u0440\u0438\u043a\u043b\u0430\u0434: ANCOVA \u0432 Python \u0412\u0438\u043a\u043b\u0430\u0434\u0430\u0447 \u0445\u043e\u0447\u0435 \u0437\u043d\u0430\u0442\u0438, \u0447\u0438 \u0442\u0440\u0438 \u0440\u0456\u0437\u043d\u0456 \u043c\u0435\u0442\u043e\u0434\u0438 \u043d\u0430\u0432\u0447\u0430\u043d\u043d\u044f \u0432\u043f\u043b\u0438\u0432\u0430\u044e\u0442\u044c \u043d\u0430 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 \u0456\u0441\u043f\u0438\u0442\u0443, \u0430\u043b\u0435 \u0432\u0456\u043d \u0445\u043e\u0447\u0435 \u0432\u0437\u044f\u0442\u0438 \u0434\u043e \u0443\u0432\u0430\u0433\u0438 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python - Statorials<\/title>\n<meta name=\"description\" content=\"\u041f\u0440\u043e\u0441\u0442\u0435 \u043f\u043e\u044f\u0441\u043d\u0435\u043d\u043d\u044f \u0442\u043e\u0433\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python.\" \/>\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\/uk\/\u0430\u043d\u043a\u043e\u0432\u0430-\u043f\u0456\u0442\u043e\u043d\/\" \/>\n<meta property=\"og:locale\" content=\"uk_UA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u041f\u0440\u043e\u0441\u0442\u0435 \u043f\u043e\u044f\u0441\u043d\u0435\u043d\u043d\u044f \u0442\u043e\u0433\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 ANCOVA \u0432 Python.\" \/>\n<meta property=\"og:url\" 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