{"id":1288,"date":"2023-07-27T00:21:15","date_gmt":"2023-07-27T00:21:15","guid":{"rendered":"https:\/\/statorials.org\/it\/cramer-v-in-python\/"},"modified":"2023-07-27T00:21:15","modified_gmt":"2023-07-27T00:21:15","slug":"cramer-v-in-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/it\/cramer-v-in-python\/","title":{"rendered":"Come calcolare la v di cramer in python"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>La V di Cramer<\/strong> \u00e8 una misura della forza dell&#8217;associazione tra due variabili nominali.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Va da 0 a 1 dove:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong> indica nessuna associazione tra le due variabili.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong> indica una forte associazione tra le due variabili.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Viene calcolato come segue:<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">V di Cramer = \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;\">Oro:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>X <sup>2<\/sup> :<\/strong> La statistica del Chi quadrato<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>n:<\/strong> dimensione totale del campione<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>r:<\/strong> numero di righe<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>c:<\/strong> Numero di colonne<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Questo tutorial fornisce alcuni esempi di calcolo della V di Cramer per una tabella di contingenza in Python.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Esempio 1: V di Cramer per una tabella 2\u00d72<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Il codice seguente mostra come calcolare la V di Cramer per una tabella 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;\">La V di Cramer risulta essere <strong>0,1617<\/strong> , il che indica un&#8217;associazione abbastanza debole tra le due variabili nella tabella.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Esempio 2: V di Cramer per tabelle pi\u00f9 grandi<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Nota che possiamo usare la funzione <strong>CramerV<\/strong> per calcolare la V di Cramer per un array di qualsiasi dimensione.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Il codice seguente mostra come calcolare la V di Cramer per una tabella con 2 righe e 3 colonne:<\/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;\">La V di Cramer risulta essere <strong>0,1775<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">Tieni presente che in questo esempio \u00e8 stata utilizzata una tabella con 2 righe e 3 colonne, ma lo stesso identico codice funziona per una tabella di qualsiasi dimensione.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Risorse addizionali<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/it\/python-per-il-test-di-indipendenza-del-chi-quadrato\/\" target=\"_blank\" rel=\"noopener\">Test di indipendenza del Chi quadrato in Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/bonta-del-chi-quadrato-del-fit-test-pitone\/\" target=\"_blank\" rel=\"noopener\">Test della bont\u00e0 di adattamento del chi quadrato in Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/test-esatto-del-pitone-dei-pescatori\/\" target=\"_blank\" rel=\"noopener\">Test esatto di Fisher in Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>La V di Cramer \u00e8 una misura della forza dell&#8217;associazione tra due variabili nominali. Va da 0 a 1 dove: 0 indica nessuna associazione tra le due variabili. 1 indica una forte associazione tra le due variabili. Viene calcolato come segue: V di Cramer = \u221a (X 2 \/n) \/ min(c-1, r-1) Oro: X 2 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Come calcolare la V di Cramer in Python - Statorials<\/title>\n<meta name=\"description\" content=\"Questo tutorial spiega come calcolare la V di Cramer in Python, con un esempio.\" \/>\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\/it\/cramer-v-in-python\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Come calcolare la V di Cramer in Python - Statorials\" \/>\n<meta property=\"og:description\" content=\"Questo tutorial spiega come calcolare la V di Cramer in Python, con un esempio.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/it\/cramer-v-in-python\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-27T00:21:15+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minuti\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/it\/cramer-v-in-python\/\",\"url\":\"https:\/\/statorials.org\/it\/cramer-v-in-python\/\",\"name\":\"Come calcolare la V di Cramer in Python - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/it\/#website\"},\"datePublished\":\"2023-07-27T00:21:15+00:00\",\"dateModified\":\"2023-07-27T00:21:15+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\"},\"description\":\"Questo tutorial spiega come calcolare la V di Cramer in Python, con un esempio.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/it\/cramer-v-in-python\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/it\/cramer-v-in-python\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/it\/cramer-v-in-python\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Casa\",\"item\":\"https:\/\/statorials.org\/it\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Come calcolare la v di cramer in python\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/it\/#website\",\"url\":\"https:\/\/statorials.org\/it\/\",\"name\":\"Statorials\",\"description\":\"La tua guida all&#039;alfabetizzazione statistica!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/it\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"it-IT\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"it-IT\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Ciao, sono Benjamin, un professore di statistica in pensione diventato insegnante dedicato di Statorials. 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