{"id":1284,"date":"2023-07-27T00:21:15","date_gmt":"2023-07-27T00:21:15","guid":{"rendered":"https:\/\/statorials.org\/uk\/cramers-v-%d0%bd%d0%b0-python\/"},"modified":"2023-07-27T00:21:15","modified_gmt":"2023-07-27T00:21:15","slug":"cramers-v-%d0%bd%d0%b0-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/cramers-v-%d0%bd%d0%b0-python\/","title":{"rendered":"\u042f\u043a \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 v \u043a\u0440\u0430\u043c\u0435\u0440\u0430 \u0432 python"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>V \u041a\u0440\u0430\u043c\u0435\u0440\u0430<\/strong> \u0454 \u043c\u0456\u0440\u043e\u044e \u043c\u0456\u0446\u043d\u043e\u0441\u0442\u0456 \u0437\u0432&#8217;\u044f\u0437\u043a\u0443 \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u043d\u043e\u043c\u0456\u043d\u0430\u043b\u044c\u043d\u0438\u043c\u0438 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412\u0456\u043d \u0437\u043c\u0456\u043d\u044e\u0454\u0442\u044c\u0441\u044f \u0432\u0456\u0434 0 \u0434\u043e 1, \u0434\u0435:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> \u043e\u0437\u043d\u0430\u0447\u0430\u0454 \u0432\u0456\u0434\u0441\u0443\u0442\u043d\u0456\u0441\u0442\u044c \u0437\u0432\u2019\u044f\u0437\u043a\u0443 \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> \u0432\u043a\u0430\u0437\u0443\u0454 \u043d\u0430 \u0441\u0438\u043b\u044c\u043d\u0438\u0439 \u0437\u0432\u2019\u044f\u0437\u043e\u043a \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0412\u0456\u043d \u0440\u043e\u0437\u0440\u0430\u0445\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f \u0442\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c:<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 = \u221a <span style=\"border-top: 1px solid black;\">(X <sup>2<\/sup> \/n) \/ \u0445\u0432 (c-1, r-1)<\/span><\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\">\u0437\u043e\u043b\u043e\u0442\u043e:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>X <sup>2<\/sup> :<\/strong> \u0421\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0430 \u0445\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>n:<\/strong> \u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0438\u0439 \u0440\u043e\u0437\u043c\u0456\u0440 \u0432\u0438\u0431\u0456\u0440\u043a\u0438<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>r:<\/strong> \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u0440\u044f\u0434\u043a\u0456\u0432<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>c:<\/strong> \u041a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443 \u043d\u0430\u0432\u0435\u0434\u0435\u043d\u043e \u043a\u0456\u043b\u044c\u043a\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456\u0432 \u043e\u0431\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044f V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0434\u043b\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u043d\u0435\u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0435\u043d\u0438\u0445 \u0441\u0438\u0442\u0443\u0430\u0446\u0456\u0439 \u0443 Python.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0434\u043b\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0456 2\u00d72<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0434\u043b\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0456 2&#215;2:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load necessary packages and functions\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">as<\/span> stats<\/span>\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np<\/span>\n\n#create 2x2 table\n<\/span>data = np. <span style=\"color: #3366ff;\">array<\/span> ([[7,12], [9,8]])\n\n<span style=\"color: #008080;\">#Chi-squared test statistic, sample size, and minimum of rows and columns\n<\/span>X2 = stats. <span style=\"color: #3366ff;\">chi2_contingency<\/span> (data, correction= <span style=\"color: #008000;\">False<\/span> )[0]\nn = np. <span style=\"color: #3366ff;\">sum<\/span> (data)\nminDim = min( <span style=\"color: #3366ff;\">data.shape<\/span> )-1\n\n<span style=\"color: #008080;\">#calculate Cramer's V<\/span>\nV = np. <span style=\"color: #3366ff;\">sqrt<\/span> ((X2\/n) \/ minDim)\n\n<span style=\"color: #008080;\">#display Cramer's V\n<\/span>print(V)\n\n0.1617<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u0438\u044f\u0432\u043b\u044f\u0454\u0442\u044c\u0441\u044f V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 <strong>0,1617<\/strong> , \u0449\u043e \u0432\u043a\u0430\u0437\u0443\u0454 \u043d\u0430 \u0434\u043e\u0441\u0438\u0442\u044c \u0441\u043b\u0430\u0431\u043a\u0438\u0439 \u0437\u0432\u2019\u044f\u0437\u043e\u043a \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438 \u0432 \u0442\u0430\u0431\u043b\u0438\u0446\u0456.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 2: V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0434\u043b\u044f \u0432\u0435\u043b\u0438\u043a\u0438\u0445 \u0442\u0430\u0431\u043b\u0438\u0446\u044c<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0417\u0432\u0435\u0440\u043d\u0456\u0442\u044c \u0443\u0432\u0430\u0433\u0443, \u0449\u043e \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>CramerV<\/strong> \u0434\u043b\u044f \u043e\u0431\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044f V Cramer \u0434\u043b\u044f \u043c\u0430\u0441\u0438\u0432\u0443 \u0431\u0443\u0434\u044c-\u044f\u043a\u043e\u0433\u043e \u0440\u043e\u0437\u043c\u0456\u0440\u0443.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0434\u043b\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u0437 2 \u0440\u044f\u0434\u043a\u0430\u043c\u0438 \u0442\u0430 3 \u0441\u0442\u043e\u0432\u043f\u0446\u044f\u043c\u0438:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load necessary packages and functions\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">as<\/span> stats<\/span>\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np<\/span>\n\n#create 2x2 table\n<\/span>data = np. <span style=\"color: #3366ff;\">array<\/span> ([[6,9], [8, 5], [12, 9]])\n\n<span style=\"color: #008080;\">#Chi-squared test statistic, sample size, and minimum of rows and columns\n<\/span>X2 = stats. <span style=\"color: #3366ff;\">chi2_contingency<\/span> (data, correction= <span style=\"color: #008000;\">False<\/span> )[0]\nn = np. <span style=\"color: #3366ff;\">sum<\/span> (data)\nminDim = min( <span style=\"color: #3366ff;\">data.shape<\/span> )-1\n\n<span style=\"color: #008080;\">#calculate Cramer's V<\/span>\nV = np. <span style=\"color: #3366ff;\">sqrt<\/span> ((X2\/n) \/ minDim)\n\n<span style=\"color: #008080;\">#display Cramer's V\n<\/span>print(V)\n\n0.1775<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0432\u0438\u044f\u0432\u043b\u044f\u0454\u0442\u044c\u0441\u044f <strong>0,1775<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u0432 \u0446\u044c\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043e \u0442\u0430\u0431\u043b\u0438\u0446\u044e \u0437 2 \u0440\u044f\u0434\u043a\u0430\u043c\u0438 \u0442\u0430 3 \u0441\u0442\u043e\u0432\u043f\u0446\u044f\u043c\u0438, \u0430\u043b\u0435 \u0442\u043e\u0439 \u0441\u0430\u043c\u0438\u0439 \u043a\u043e\u0434 \u043f\u0440\u0430\u0446\u044e\u0454 \u0434\u043b\u044f \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u0431\u0443\u0434\u044c-\u044f\u043a\u0438\u0445 \u0440\u043e\u0437\u043c\u0456\u0440\u0456\u0432.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/uk\/\u0442\u0435\u0441\u0442-\u043d\u0435\u0437\u0430\u043b\u0435\u0436\u043d\u043e\u0441\u0442\u0456-\u0445\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442-python\/\" target=\"_blank\" rel=\"noopener\">\u0422\u0435\u0441\u0442 \u043d\u0435\u0437\u0430\u043b\u0435\u0436\u043d\u043e\u0441\u0442\u0456 \u0425\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442 \u0443 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0445\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442-\u0442\u0435\u0441\u0442-\u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u043e\u0441\u0442\u0456-python\/\" target=\"_blank\" rel=\"noopener\">\u041f\u0435\u0440\u0435\u0432\u0456\u0440\u043a\u0430 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u043e\u0441\u0442\u0456 \u0445\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442 \u0443 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0442\u043e\u0447\u043d\u0438\u0438-\u0442\u0435\u0441\u0442-\u0440\u0438\u0431\u0430\u043b\u044c\u0441\u044c\u043a\u043e\u0433\u043e-\u043f\u0456\u0442\u043e\u043d\u0430\/\" target=\"_blank\" rel=\"noopener\">\u0422\u043e\u0447\u043d\u0438\u0439 \u0442\u0435\u0441\u0442 \u0424\u0456\u0448\u0435\u0440\u0430 \u0432 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 \u0454 \u043c\u0456\u0440\u043e\u044e \u043c\u0456\u0446\u043d\u043e\u0441\u0442\u0456 \u0437\u0432&#8217;\u044f\u0437\u043a\u0443 \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u043d\u043e\u043c\u0456\u043d\u0430\u043b\u044c\u043d\u0438\u043c\u0438 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438. \u0412\u0456\u043d \u0437\u043c\u0456\u043d\u044e\u0454\u0442\u044c\u0441\u044f \u0432\u0456\u0434 0 \u0434\u043e 1, \u0434\u0435: 0 \u043e\u0437\u043d\u0430\u0447\u0430\u0454 \u0432\u0456\u0434\u0441\u0443\u0442\u043d\u0456\u0441\u0442\u044c \u0437\u0432\u2019\u044f\u0437\u043a\u0443 \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438. 1 \u0432\u043a\u0430\u0437\u0443\u0454 \u043d\u0430 \u0441\u0438\u043b\u044c\u043d\u0438\u0439 \u0437\u0432\u2019\u044f\u0437\u043e\u043a \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438. \u0412\u0456\u043d \u0440\u043e\u0437\u0440\u0430\u0445\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f \u0442\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c: V \u041a\u0440\u0430\u043c\u0435\u0440\u0430 = \u221a (X 2 \/n) \/ \u0445\u0432 (c-1, r-1) \u0437\u043e\u043b\u043e\u0442\u043e: X 2 : \u0421\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0430 \u0445\u0456-\u043a\u0432\u0430\u0434\u0440\u0430\u0442 n: \u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0438\u0439 [&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 \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 V 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