{"id":1286,"date":"2023-07-27T00:21:15","date_gmt":"2023-07-27T00:21:15","guid":{"rendered":"https:\/\/statorials.org\/ja\/python-%e3%81%ae%e3%82%af%e3%83%a9%e3%83%9e%e3%83%bc%e3%82%b9%e3%82%99-v\/"},"modified":"2023-07-27T00:21:15","modified_gmt":"2023-07-27T00:21:15","slug":"python-%e3%81%ae%e3%82%af%e3%83%a9%e3%83%9e%e3%83%bc%e3%82%b9%e3%82%99-v","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python-%e3%81%ae%e3%82%af%e3%83%a9%e3%83%9e%e3%83%bc%e3%82%b9%e3%82%99-v\/","title":{"rendered":"Python \u3067 cramer&#39;s v \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>Cramer&#8217;s V \u306f\u3001<\/strong> 2 \u3064\u306e\u540d\u76ee\u5909\u6570\u9593\u306e\u95a2\u9023\u306e\u5f37\u3055\u306e\u5c3a\u5ea6\u3067\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">0 \u304b\u3089 1 \u307e\u3067\u5909\u5316\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0 \u306f\u3001<\/strong> 2 \u3064\u306e\u5909\u6570\u9593\u306b\u95a2\u9023\u6027\u304c\u306a\u3044\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1 \u306f\u3001<\/strong> 2 \u3064\u306e\u5909\u6570\u9593\u306e\u5f37\u3044\u95a2\u9023\u6027\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u3088\u3046\u306b\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u30af\u30e9\u30de\u30fc\u306e V = \u221a <span style=\"border-top: 1px solid black;\">(X <sup>2<\/sup> \/n) \/ min(c-1, r-1)<\/span><\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>X <sup>2<\/sup> :<\/strong>\u30ab\u30a4\u4e8c\u4e57\u7d71\u8a08\u91cf<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>n:<\/strong>\u5408\u8a08\u30b5\u30f3\u30d7\u30eb\u30b5\u30a4\u30ba<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>r:<\/strong>\u884c\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>c:<\/strong>\u5217\u6570<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u5206\u5272\u8868\u306e Cramer&#8217;s V \u3092\u8a08\u7b97\u3059\u308b\u4f8b\u3092\u3044\u304f\u3064\u304b\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 1: 2\u00d72 \u30c6\u30fc\u30d6\u30eb\u306e Cramer \u306e V<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012&#215;2 \u30c6\u30fc\u30d6\u30eb\u306e Cramer&#8217;s V \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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;\">Cramer \u306e V \u306f<strong>0.1617<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u3001\u3053\u308c\u306f\u8868\u5185\u306e 2 \u3064\u306e\u5909\u6570\u9593\u306e\u95a2\u9023\u6027\u304c\u304b\u306a\u308a\u5f31\u3044\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b 2: \u5927\u304d\u306a\u30c6\u30fc\u30d6\u30eb\u306e\u5834\u5408\u306f Cramer&#8217;s V<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\"><strong>CramerV<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u4efb\u610f\u306e\u30b5\u30a4\u30ba\u306e\u914d\u5217\u306e Cramer \u306e V \u3092\u8a08\u7b97\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u30012 \u884c 3 \u5217\u306e\u30c6\u30fc\u30d6\u30eb\u306e Cramer&#8217;s V \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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;\">Cramer \u306e V \u306f<strong>0.1775<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4f8b\u3067\u306f 2 \u884c 3 \u5217\u306e\u30c6\u30fc\u30d6\u30eb\u3092\u4f7f\u7528\u3057\u307e\u3057\u305f\u304c\u3001\u307e\u3063\u305f\u304f\u540c\u3058\u30b3\u30fc\u30c9\u304c\u3069\u306e\u6b21\u5143\u306e\u30c6\u30fc\u30d6\u30eb\u3067\u3082\u6a5f\u80fd\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/ja\/\u30ab\u30a4\u4e8c\u4e57\u72ec\u7acb\u6027\u30c6\u30b9\u30c8python\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u306e\u30ab\u30a4 2 \u4e57\u72ec\u7acb\u6027\u30c6\u30b9\u30c8<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30ab\u30a4\u4e8c\u4e57\u9069\u5408\u5ea6\u30c6\u30b9\u30c8python\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u306e\u30ab\u30a4\u4e8c\u4e57\u9069\u5408\u5ea6\u691c\u5b9a<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u6f01\u5e2b\u306e-python-\u306e\u6b63\u78ba\u306a\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u306e\u30d5\u30a3\u30c3\u30b7\u30e3\u30fc\u306e\u6b63\u78ba\u691c\u5b9a<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cramer&#8217;s V \u306f\u3001 2 \u3064\u306e\u540d\u76ee\u5909\u6570\u9593\u306e\u95a2\u9023\u306e\u5f37\u3055\u306e\u5c3a\u5ea6\u3067\u3059\u3002 0 \u304b\u3089 1 \u307e\u3067\u5909\u5316\u3057\u307e\u3059\u3002 0 \u306f\u3001 2 \u3064\u306e\u5909\u6570\u9593\u306b\u95a2\u9023\u6027\u304c\u306a\u3044\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002 1 \u306f\u3001 2 \u3064\u306e\u5909\u6570\u9593\u306e\u5f37\u3044\u95a2\u9023\u6027\u3092\u793a\u3057\u307e\u3059\u3002 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1286","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python \u3067 Cramer&#039;s V \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5 - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067 Cramer&#039;s V \u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\u3092\u4f8b\u3092\u6319\u3052\u3066\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\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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