{"id":914,"date":"2023-07-28T08:16:47","date_gmt":"2023-07-28T08:16:47","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%81%8f%e7%9b%b8%e5%85%b3r\/"},"modified":"2023-07-28T08:16:47","modified_gmt":"2023-07-28T08:16:47","slug":"%e5%81%8f%e7%9b%b8%e5%85%b3r","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%81%8f%e7%9b%b8%e5%85%b3r\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u8ba1\u7b97\u504f\u76f8\u5173"},"content":{"rendered":"

<\/p>\n

\n

\u5728\u7edf\u8ba1\u5b66\u4e2d\uff0c\u6211\u4eec\u7ecf\u5e38\u4f7f\u7528\u76ae\u5c14\u900a\u76f8\u5173\u7cfb\u6570<\/a>\u6765\u8861\u91cf\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u7ebf\u6027\u5173\u7cfb\u3002<\/span><\/p>\n

\u7136\u800c\uff0c\u6709\u65f6\u6211\u4eec\u60f3\u5728\u63a7\u5236\u7b2c\u4e09\u4e2a\u53d8\u91cf\u7684\u540c\u65f6<\/strong>\u4e86\u89e3\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/p>\n

\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u60f3\u8981\u8861\u91cf\u5b66\u751f\u7684\u5b66\u4e60\u65f6\u6570\u4e0e\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u5173\u8054\uff0c\u540c\u65f6\u63a7\u5236\u5b66\u751f\u5728\u73ed\u7ea7\u4e2d\u7684\u5f53\u524d\u6210\u7ee9\u3002<\/span><\/p>\n

\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u504f\u76f8\u5173<\/strong>\u6765\u8861\u91cf\u5b66\u4e60\u65f6\u95f4\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/p>\n

\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 R \u4e2d\u8ba1\u7b97\u504f\u76f8\u5173\u3002<\/span><\/p>\n

\u793a\u4f8b\uff1aR \u4e2d\u7684\u504f\u76f8\u5173<\/strong><\/span><\/h2>\n

\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u6570\u636e\u6846\uff0c\u663e\u793a 10 \u540d\u5b66\u751f\u7684\u5f53\u524d\u6210\u7ee9\u3001\u5b66\u4e60\u603b\u65f6\u6570\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\uff1a<\/span><\/p>\n

 #create data frame<\/span>\ndf <- data. frame<\/span> (currentGrade = c(82, 88, 75, 74, 93, 97, 83, 90, 90, 80),\n                 hours = c(4, 3, 6, 5, 4, 5, 8, 7, 4, 6),\n                 examScore = c(88, 85, 76, 70, 92, 94, 89, 85, 90, 93))\n\n#view data frame\n<\/span>df\n\n   currentGrade hours examScore\n1 82 4 88\n2 88 3 85\n3 75 6 76\n4 74 5 70\n5 93 4 92\n6 97 5 94\n7 83 8 89\n8 90 7 85\n9 90 4 90\n10 80 6 93\n<\/strong><\/pre>\n
 library<\/span> (ppcor)<\/span>\n\n#calculate partial correlations<\/span>\npcor(df)\n\n$estimate\n             currentGrade hours examScore\ncurrentGrade 1.0000000 -0.3112341 0.7355673\nhours -0.3112341 1.0000000 0.1906258\nexamScore 0.7355673 0.1906258 1.0000000\n\n$p.value\n             currentGrade hours examScore\ncurrentGrade 0.00000000 0.4149353 0.02389896\nhours 0.41493532 0.0000000 0.62322848\nexamScore 0.02389896 0.6232285 0.00000000\n\n$statistic\n             currentGrade hours examScore\ncurrentGrade 0.0000000 -0.8664833 2.8727185\nhours -0.8664833 0.0000000 0.5137696\nexamScore 2.8727185 0.5137696 0.0000000\n\n$n\n[1] 10\n\n$gp\n[1] 1\n\n$method\n[1] \"pearson\"\n<\/strong><\/pre>\n
\u4ee5\u4e0b\u662f\u5982\u4f55\u89e3\u91ca\u7ed3\u679c\uff1a<\/span><\/p>\n
\u5b66\u4e60\u65f6\u95f4\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u90e8\u5206\u76f8\u5173\u6027\uff1a<\/strong><\/span><\/p>\n
\u5b66\u4e60\u65f6\u95f4\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u504f\u76f8\u5173\u4e3a0.191<\/strong> \uff0c\u5448\u73b0\u8f83\u5c0f\u7684\u6b63\u76f8\u5173\u3002\u968f\u7740\u5b66\u4e60\u65f6\u95f4\u7684\u589e\u52a0\uff0c\u5047\u8bbe\u5f53\u524d\u6210\u7ee9\u4fdd\u6301\u4e0d\u53d8\uff0c\u8003\u8bd5\u6210\u7ee9\u4e5f\u5f80\u5f80\u4f1a\u589e\u52a0\u3002<\/span><\/p>\n
\u6b64\u504f\u76f8\u5173\u7684 p \u503c\u4e3a0.623<\/strong> \uff0c\u5728 \u03b1 = 0.05 \u65f6\u4e0d\u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u3002<\/span><\/p>\n
\u5f53\u524d\u6210\u7ee9\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u90e8\u5206\u76f8\u5173\u6027\uff1a<\/strong><\/span><\/p>\n
\u5f53\u524d\u6210\u7ee9\u4e0e\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u504f\u76f8\u5173\u6027\u4e3a0.736<\/strong> \uff0c\u5448\u73b0\u5f88\u5f3a\u7684\u6b63\u76f8\u5173\u6027\u3002\u968f\u7740\u5f53\u524d\u6210\u7ee9\u7684\u63d0\u9ad8\uff0c\u5047\u8bbe\u5b66\u4e60\u65f6\u6570\u4fdd\u6301\u4e0d\u53d8\uff0c\u8003\u8bd5\u6210\u7ee9\u4e5f\u5f80\u5f80\u4f1a\u589e\u52a0\u3002<\/span><\/p>\n
\u6b64\u504f\u76f8\u5173\u7684 p \u503c\u4e3a0.024<\/strong> \uff0c\u5728 \u03b1 = 0.05 \u65f6\u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u3002<\/span><\/p>\n
\u5f53\u524d\u5e74\u7ea7\u548c\u5b66\u4e60\u65f6\u95f4\u4e4b\u95f4\u7684\u504f\u76f8\u5173\uff1a<\/strong><\/span><\/p>\n
\u5f53\u524d\u6210\u7ee9\u3001\u5b66\u4e60\u65f6\u95f4\u548c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4e4b\u95f4\u7684\u504f\u76f8\u5173\u4e3a-0.311<\/strong> \uff0c\u8868\u793a\u8f7b\u5fae\u7684\u8d1f\u76f8\u5173\u3002\u968f\u7740\u5f53\u524d\u6210\u7ee9\u7684\u589e\u52a0\uff0c\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u5f80\u5f80\u4f1a\u4e0b\u964d\uff0c\u5047\u8bbe\u671f\u672b\u8003\u8bd5\u6210\u7ee9\u4fdd\u6301\u4e0d\u53d8\u3002<\/span><\/p>\n
\u6b64\u504f\u76f8\u5173\u7684p \u503c\u4e3a<\/a>0.415<\/strong> \uff0c\u5728 \u03b1 = 0.05 \u65f6\u4e0d\u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u3002<\/span><\/p>\n
\u7ed3\u679c\u8fd8\u544a\u8bc9\u6211\u4eec\uff0c\u8ba1\u7b97\u504f\u76f8\u5173\u7684\u65b9\u6cd5\u662f\u201cPearson\u201d\u3002<\/span><\/p>\n
\u5728pcor()<\/strong>\u51fd\u6570\u4e2d\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u6307\u5b9a\u201ckendall\u201d\u6216\u201cpearson\u201d\u4f5c\u4e3a\u8ba1\u7b97\u76f8\u5173\u6027\u7684\u66ff\u4ee3\u65b9\u6cd5\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u4efb\u52a1\uff1a<\/span><\/p>\n
 \u5982\u4f55\u5728 R \u4e2d\u8ba1\u7b97 Spearman \u7b49\u7ea7\u76f8\u5173<\/a>
\u5982\u4f55\u8ba1\u7b97 R \u4e2d\u7684\u4e92\u76f8\u5173<\/a>
\u5982\u4f55\u8ba1\u7b97R\u4e2d\u7684\u6ed1\u52a8\u76f8\u5173\u6027<\/a>
\u5982\u4f55\u8ba1\u7b97 R \u4e2d\u7684\u70b9\u53cc\u5217\u76f8\u5173\u6027<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u5728\u7edf\u8ba1\u5b66\u4e2d\uff0c\u6211\u4eec\u7ecf\u5e38\u4f7f\u7528\u76ae\u5c14\u900a\u76f8\u5173\u7cfb\u6570\u6765\u8861\u91cf\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u7ebf\u6027\u5173\u7cfb\u3002 \u7136\u800c\uff0c\u6709\u65f6\u6211\u4eec\u60f3\u5728\u63a7\u5236\u7b2c\u4e09\u4e2a\u53d8\u91cf\u7684\u540c\u65f6\u4e86 […]<\/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":[],"class_list":["post-914","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 R - Statorials \u4e2d\u8ba1\u7b97\u504f\u76f8\u5173<\/title>\n<meta name=\"description\" content=\"\u901a\u8fc7\u793a\u4f8b\u7b80\u5355\u89e3\u91ca\u5982\u4f55\u5728 R \u4e2d\u8ba1\u7b97\u504f\u76f8\u5173\u3002\" \/>\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\/cn\/\u504f\u76f8\u5173r\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u5728 R - 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