{"id":546,"date":"2023-07-29T13:35:37","date_gmt":"2023-07-29T13:35:37","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e8%be%be%e8%af%ba%e7%93%a6%e5%81%87%e8%ae%be\/"},"modified":"2023-07-29T13:35:37","modified_gmt":"2023-07-29T13:35:37","slug":"%e8%be%be%e8%af%ba%e7%93%a6%e5%81%87%e8%ae%be","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e8%be%be%e8%af%ba%e7%93%a6%e5%81%87%e8%ae%be\/","title":{"rendered":"\u5982\u4f55\u68c0\u67e5\u65b9\u5dee\u5206\u6790\u5047\u8bbe"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u5355\u5411\u65b9\u5dee\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">\u5355\u5411\u65b9\u5dee\u5206\u6790<\/a>\u662f\u4e00\u79cd\u7edf\u8ba1\u68c0\u9a8c\uff0c\u7528\u4e8e\u786e\u5b9a\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u6211\u4eec\u4f55\u65f6\u53ef\u4ee5\u4f7f\u7528\u5355\u5411\u65b9\u5dee\u5206\u6790\u7684\u793a\u4f8b\uff1a<\/span><\/p>\n<blockquote>\n<p><span style=\"color: #000000;\">\u60a8\u5c06\u4e00\u4e2a\u7531 90 \u540d\u5b66\u751f\u7ec4\u6210\u7684\u73ed\u7ea7\u968f\u673a\u5206\u4e3a\u4e09\u7ec4\uff0c\u6bcf\u7ec4 30 \u4eba\u3002\u6bcf\u7ec4\u4f7f\u7528\u4e0d\u540c\u7684\u5b66\u4e60\u6280\u5de7\u4e00\u4e2a\u6708\u6765\u51c6\u5907\u8003\u8bd5\u3002\u6708\u5e95\uff0c\u6240\u6709\u5b66\u751f\u53c2\u52a0\u76f8\u540c\u7684\u8003\u8bd5\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u60a8\u60f3\u77e5\u9053\u5b66\u4e60\u6280\u5de7\u662f\u5426\u4f1a\u5f71\u54cd\u8003\u8bd5\u6210\u7ee9\u3002\u56e0\u6b64\uff0c\u60a8\u6267\u884c<strong>\u5355\u5411\u65b9\u5dee\u5206\u6790<\/strong>\u6765\u786e\u5b9a\u4e09\u7ec4\u7684\u5e73\u5747\u5206\u6570\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<\/blockquote>\n<p><span style=\"color: #000000;\">\u5728\u6267\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790\u4e4b\u524d\uff0c\u6211\u4eec\u5fc5\u987b\u9996\u5148\u9a8c\u8bc1\u662f\u5426\u6ee1\u8db3\u4e09\u4e2a\u5047\u8bbe\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u6b63\u6001\u6027<\/strong>\u2014\u2014\u6bcf\u4e2a\u6837\u672c\u90fd\u662f\u4ece\u6b63\u6001\u5206\u5e03\u7684\u603b\u4f53\u4e2d\u62bd\u53d6\u7684\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \u65b9\u5dee\u76f8\u7b49<\/strong>\u2014\u2014\u62bd\u53d6\u6837\u672c\u7684\u603b\u4f53\u65b9\u5dee\u76f8\u7b49\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. \u72ec\u7acb\u6027<\/strong>\u2014\u2014\u5404\u7ec4\u5185\u7684\u89c2\u5bdf\u7ed3\u679c\u5f7c\u6b64\u72ec\u7acb\uff0c\u5e76\u4e14\u7ec4\u5185\u7684\u89c2\u5bdf\u7ed3\u679c<\/span><span style=\"color: #000000;\">\u662f\u901a\u8fc7\u968f\u673a\u62bd\u6837\u83b7\u5f97\u7684\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u4e0d\u6ee1\u8db3\u8fd9\u4e9b\u5047\u8bbe\uff0c\u6211\u4eec\u7684\u5355\u5411\u65b9\u5dee\u5206\u6790\u7ed3\u679c\u53ef\u80fd\u4e0d\u53ef\u9760\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u5c06\u89e3\u91ca\u5982\u4f55\u68c0\u67e5\u8fd9\u4e9b\u5047\u8bbe\u4ee5\u53ca\u5982\u679c\u8fdd\u53cd\u5176\u4e2d\u4efb\u4f55\u5047\u8bbe\u8be5\u600e\u4e48\u529e\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5047\u8bbe#1\uff1a\u5e38\u6001<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u65b9\u5dee\u5206\u6790\u5047\u8bbe\u6bcf\u4e2a\u6837\u672c\u90fd\u662f\u4ece\u6b63\u6001\u5206\u5e03\u7684\u603b\u4f53\u4e2d\u62bd\u53d6\u7684\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u5982\u4f55\u5728 R \u4e2d\u68c0\u9a8c\u8fd9\u4e2a\u5047\u8bbe\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u9a8c\u8bc1\u8fd9\u4e2a\u5047\u8bbe\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e24\u79cd\u65b9\u6cd5\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u4f7f\u7528\u76f4\u65b9\u56fe\u6216<a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">QQ \u56fe<\/a>\u76f4\u89c2\u5730\u9a8c\u8bc1\u5047\u8bbe\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u4f7f\u7528 Shapiro-Wilk\u3001Kolmogorov-Smironov\u3001Jarque-Barre \u6216 D&#8217;Agostino-Pearson \u7b49\u6b63\u5f0f\u7edf\u8ba1\u68c0\u9a8c\u9a8c\u8bc1\u5047\u8bbe\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u62db\u52df 90 \u4eba\u53c2\u52a0\u4e00\u9879\u51cf\u80a5\u5b9e\u9a8c\uff0c\u5176\u4e2d\u6211\u4eec\u968f\u673a\u5206\u914d 30 \u4eba\u9075\u5faa\u8ba1\u5212 A\u3001\u8ba1\u5212 B \u6216\u8ba1\u5212 C\uff0c\u4e3a\u671f\u4e00\u4e2a\u6708\u3002\u4e3a\u4e86\u4e86\u89e3\u8be5\u8ba1\u5212\u662f\u5426\u5bf9\u51cf\u80a5\u6709\u5f71\u54cd\uff0c\u6211\u4eec\u60f3\u8981\u8fdb\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790\u3002\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u76f4\u65b9\u56fe\u3001QQ \u56fe\u548c Shapiro-Wilk \u68c0\u9a8c\u6765\u68c0\u67e5\u6b63\u6001\u6027\u5047\u8bbe\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u62df\u5408\u65b9\u5dee\u5206\u6790\u6a21\u578b\u3002<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<span style=\"color: #000000;\">set.seed(0)\n<\/span>\n#create data frame\n<span style=\"color: #000000;\">data &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (program = rep(c(\" <span style=\"color: #ff0000;\">A<\/span> \", \" <span style=\"color: #ff0000;\">B<\/span> \", \" <span style=\"color: #ff0000;\">C<\/span> \"), each = <span style=\"color: #008000;\">30<\/span> ),\n                   weight_loss = c(runif(30, 0, 3),\n                                   runif(30, 0, 5),\n                                   runif(30, 1, 7)))<\/span>\n\n#fit the one-way ANOVA model\n<span style=\"color: #000000;\">model &lt;- aov(weight_loss ~ program, data = data)<\/span>\n<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>2. \u521b\u5efa\u54cd\u5e94\u503c\u7684\u76f4\u65b9\u56fe\u3002<\/strong><\/span> <\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create histogram<\/span>\nhist(data$weight_loss)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-4758 size-full\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/histogramme.jpg\" alt=\"\" width=\"541\" height=\"392\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u8be5\u5206\u5e03\u770b\u8d77\u6765\u4e0d\u662f\u5f88\u6b63\u6001\u5206\u5e03\uff08\u4f8b\u5982\uff0c\u5b83\u4e0d\u662f\u201c\u949f\u5f62\u201d\u5f62\u72b6\uff09\uff0c\u4f46\u6211\u4eec\u4e5f\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a QQ \u56fe\u6765\u91cd\u65b0\u89c2\u5bdf\u8be5\u5206\u5e03\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. \u521b\u5efa\u6b8b\u5dee QQ \u56fe<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create QQ plot to compare this dataset to a theoretical normal distribution<\/span>\nqqnorm(model$residuals)\n\n<span style=\"color: #008080;\">#add straight diagonal line to plot\n<\/span>qqline(model$residuals)<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-4760 size-full\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/qqplot.jpg\" alt=\"R \u4e2d\u7684 Q-Q \u56fe\u793a\u4f8b\" width=\"557\" height=\"394\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u6765\u8bf4\uff0c\u5982\u679c\u6570\u636e\u70b9\u4f4d\u4e8e QQ \u56fe\u4e2d\u7684\u76f4\u7ebf\u5bf9\u89d2\u7ebf\u4e0a\uff0c\u5219\u6570\u636e\u96c6\u53ef\u80fd\u670d\u4ece\u6b63\u6001\u5206\u5e03\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u6cbf\u672b\u7aef\u7684\u7ebf\u6709\u660e\u663e\u7684\u504f\u5dee\uff0c\u8fd9\u53ef\u80fd\u8868\u660e\u6570\u636e\u4e0d\u5448\u6b63\u6001\u5206\u5e03\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>4. \u6267\u884c Shapiro-Wilk \u6b63\u6001\u6027\u68c0\u9a8c\u3002<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#Conduct Shapiro-Wilk Test for normality<\/span>\nshapiro. <span style=\"color: #3366ff;\">test<\/span> (data$weight_loss)\n\n#Shapiro-Wilk normality test\n#\n#data: data$weight_loss\n#W = 0.9587, p-value = 0.005999\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Shapiro-Wilk \u68c0\u9a8c\u68c0\u9a8c\u6837\u672c\u6765\u81ea\u6b63\u6001\u5206\u5e03\u7684\u539f\u5047\u8bbe\u4e0e\u6837\u672c\u4e0d\u6765\u81ea\u6b63\u6001\u5206\u5e03\u7684\u5907\u62e9\u5047\u8bbe\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u68c0\u9a8c\u7684 p \u503c\u4e3a<strong>0.005999<\/strong> \uff0c\u4f4e\u4e8e alpha \u6c34\u5e73 0.05\u3002\u8fd9\u8868\u660e\u6837\u672c\u4e0d\u670d\u4ece\u6b63\u6001\u5206\u5e03\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u5982\u679c\u4e0d\u9075\u5b88\u6b64\u5047\u8bbe\u8be5\u600e\u4e48\u529e\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u6765\u8bf4\uff0c\u53ea\u8981\u6837\u672c\u91cf\u8db3\u591f\u5927\uff0c\u5355\u5411\u65b9\u5dee\u5206\u6790\u5c31\u88ab\u8ba4\u4e3a\u5bf9\u4e8e\u8fdd\u53cd\u6b63\u6001\u6027\u5047\u8bbe\u975e\u5e38\u7a33\u5065\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b64\u5916\uff0c\u5982\u679c\u60a8\u6709\u975e\u5e38\u5927\u7684\u6837\u672c\uff0c\u50cf\u590f\u76ae\u7f57-\u5a01\u5c14\u514b\u68c0\u9a8c\u8fd9\u6837\u7684\u7edf\u8ba1\u68c0\u9a8c\u51e0\u4e4e\u603b\u662f\u4f1a\u544a\u8bc9\u60a8\u60a8\u7684\u6570\u636e\u4e0d\u6b63\u5e38\u3002\u56e0\u6b64\uff0c\u901a\u5e38\u6700\u597d\u4f7f\u7528\u76f4\u65b9\u56fe\u548c QQ \u56fe\u7b49\u56fe\u8868\u6765\u76f4\u89c2\u5730\u68c0\u67e5\u6570\u636e\u3002\u53ea\u9700\u67e5\u770b\u56fe\u8868\uff0c\u60a8\u5c31\u53ef\u4ee5\u5f88\u597d\u5730\u4e86\u89e3\u6570\u636e\u662f\u5426\u670d\u4ece\u6b63\u6001\u5206\u5e03\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u6b63\u6001\u6027\u5047\u8bbe\u88ab<em>\u4e25\u91cd<\/em>\u8fdd\u53cd\u6216\u8005\u4f60\u53ea\u662f\u60f3\u975e\u5e38\u4fdd\u5b88\uff0c\u4f60\u6709\u4e24\u79cd\u9009\u62e9\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>(1)<\/strong>\u53d8\u6362\u6570\u636e\u7684\u54cd\u5e94\u503c\uff0c\u4f7f\u5206\u5e03\u66f4\u52a0\u6b63\u6001\u5206\u5e03\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>(2)<\/strong>\u6267\u884c\u7b49\u6548\u7684\u975e\u53c2\u6570\u68c0\u9a8c\uff0c\u4f8b\u5982\u4e0d\u9700\u8981\u6b63\u6001\u6027\u5047\u8bbe\u7684<a href=\"https:\/\/statorials.org\/cn\/\u514b\u9c81\u65af\u5361\u5c14\u6c83\u5229\u65af\u68c0\u9a8c\/\" target=\"_blank\" rel=\"noopener\">Kruskal-Wallis \u68c0\u9a8c<\/a>\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5047\u8bbe#2\uff1a\u65b9\u5dee\u76f8\u7b49<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u65b9\u5dee\u5206\u6790\u5047\u8bbe\u4ece\u4e2d\u62bd\u53d6\u6837\u672c\u7684\u603b\u4f53\u7684\u65b9\u5dee\u662f\u76f8\u7b49\u7684\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u5982\u4f55\u5728 R \u4e2d\u68c0\u9a8c\u8fd9\u4e2a\u5047\u8bbe\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e24\u79cd\u65b9\u6cd5\u5728 R \u4e2d\u9a8c\u8bc1\u8fd9\u4e2a\u5047\u8bbe\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u4f7f\u7528\u7bb1\u7ebf\u56fe\u76f4\u89c2\u5730\u9a8c\u8bc1\u5047\u8bbe\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u4f7f\u7528\u6b63\u5f0f\u7684\u7edf\u8ba1\u68c0\u9a8c\uff08\u4f8b\u5982\u5df4\u7279\u5229\u7279\u68c0\u9a8c\uff09\u6765\u68c0\u9a8c\u5047\u8bbe\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u6211\u4eec\u4e4b\u524d\u521b\u5efa\u7684\u76f8\u540c\u7684\u5047\u51cf\u80a5\u6570\u636e\u96c6\u6765\u6267\u884c\u6b64\u64cd\u4f5c\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u521b\u5efa\u7bb1\u7ebf\u56fe\u3002<\/strong><\/span> <\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#Create box plots that show distribution of weight loss for each group<\/span>\nboxplot(weight_loss ~ program, xlab=' <span style=\"color: #ff0000;\">Program<\/span> ', ylab=' <span style=\"color: #ff0000;\">Weight Loss<\/span> ', data=data)\n<\/strong><\/pre>\n<h3><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-4762 size-full\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/boite-a-moustaches.jpg\" alt=\"\" width=\"557\" height=\"371\" srcset=\"\" sizes=\"auto, \"><\/h3>\n<p><span style=\"color: #000000;\">\u6bcf\u7ec4\u4f53\u91cd\u51cf\u8f7b\u7684\u65b9\u5dee\u53ef\u4ee5\u901a\u8fc7\u6bcf\u4e2a\u7bb1\u7ebf\u56fe\u7684\u957f\u5ea6\u6765\u89c2\u5bdf\u3002\u76d2\u5b50\u8d8a\u957f\uff0c\u65b9\u5dee\u5c31\u8d8a\u5927\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4e0e\u8ba1\u5212 A \u548c\u8ba1\u5212 B \u76f8\u6bd4\uff0c\u8ba1\u5212 C \u7684\u53c2\u4e0e\u8005\u7684\u65b9\u5dee\u7a0d\u9ad8\u4e00\u4e9b\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \u6267\u884c\u5df4\u7279\u5229\u7279\u68c0\u9a8c\u3002<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#Create box plots that show distribution of weight loss for each group<\/span>\nbartlett. <span style=\"color: #3366ff;\">test<\/span> (weight_loss ~ program, data=data)\n\n#Bartlett test of homogeneity of variances\n#\n#data: weight_loss by program\n#Bartlett's K-squared = 8.2713, df = 2, p-value = 0.01599<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/r-\u4e2d\u7684\u5df4\u7279\u5229\u8328\u6d4b\u8bd5\/\" target=\"_blank\" rel=\"noopener\">Bartlett \u68c0\u9a8c<\/a>\u6d4b\u8bd5\u6837\u672c\u5177\u6709\u76f8\u7b49\u65b9\u5dee\u7684\u539f\u5047\u8bbe\u4e0e\u6837\u672c\u4e0d\u5177\u6709\u76f8\u7b49\u65b9\u5dee\u7684\u5907\u62e9\u5047\u8bbe\u3002\u5728\u672c\u4f8b\u4e2d\uff0c\u68c0\u9a8c\u7684 p \u503c\u4e3a<strong>0.01599<\/strong> \uff0c\u4f4e\u4e8e alpha \u6c34\u5e73 0.05\u3002\u8fd9\u8868\u660e\u6837\u672c\u5e76\u4e0d\u90fd\u5177\u6709\u76f8\u540c\u7684\u65b9\u5dee\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u5982\u679c\u4e0d\u9075\u5b88\u6b64\u5047\u8bbe\u8be5\u600e\u4e48\u529e\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u6765\u8bf4\uff0c<\/span><span style=\"color: #000000;\">\u53ea\u8981\u6bcf\u7ec4\u5177\u6709\u76f8\u540c\u7684\u6837\u672c\u91cf\uff0c\u5355\u5411\u65b9\u5dee\u5206\u6790\u5c31\u88ab\u8ba4\u4e3a\u5bf9\u4e8e\u8fdd\u53cd\u7b49\u65b9\u5dee\u5047\u8bbe\u76f8\u5f53\u7a33\u5065\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f46\u662f\uff0c\u5982\u679c\u6837\u672c\u5927\u5c0f\u4e0d\u76f8\u540c\u5e76\u4e14\u4e25\u91cd\u8fdd\u53cd\u4e86\u8fd9\u4e00\u5047\u8bbe\uff0c\u60a8\u53ef\u4ee5\u6539\u4e3a\u8fd0\u884c<a href=\"https:\/\/statorials.org\/cn\/\u514b\u9c81\u65af\u5361\u5c14\u6c83\u5229\u65af\u68c0\u9a8c\/\" target=\"_blank\" rel=\"noopener\">Kruskal-Wallis \u68c0\u9a8c<\/a>\uff0c\u8fd9\u662f\u5355\u5411\u65b9\u5dee\u5206\u6790\u7684\u975e\u53c2\u6570\u7248\u672c\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5047\u8bbe#3\uff1a\u72ec\u7acb\u6027<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u65b9\u5dee\u5206\u6790\u5047\u8bbe\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6bcf\u7ec4\u7684\u89c2\u5bdf\u7ed3\u679c\u72ec\u7acb\u4e8e\u6240\u6709\u5176\u4ed6\u7ec4\u7684\u89c2\u5bdf\u7ed3\u679c\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6bcf\u7ec4\u5185\u7684\u89c2\u5bdf\u7ed3\u679c\u662f\u901a\u8fc7\u968f\u673a\u6837\u672c\u83b7\u5f97\u7684\u3002<\/span><\/li>\n<\/ul>\n<h3><strong><span style=\"color: #000000;\">\u5982\u4f55\u9a8c\u8bc1\u8fd9\u4e2a\u5047\u8bbe\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u6ca1\u6709\u6b63\u5f0f\u7684\u6d4b\u8bd5\u53ef\u4ee5\u7528\u6765\u9a8c\u8bc1\u6bcf\u7ec4\u4e2d\u7684\u89c2\u5bdf\u7ed3\u679c\u662f\u72ec\u7acb\u7684\u5e76\u4e14\u5b83\u4eec\u662f\u901a\u8fc7\u968f\u673a\u6837\u672c\u83b7\u5f97\u7684\u3002<\/span><span style=\"color: #000000;\">\u6ee1\u8db3\u8fd9\u4e00\u5047\u8bbe\u7684\u552f\u4e00\u65b9\u6cd5\u662f\u4f7f\u7528\u968f\u673a\u8bbe\u8ba1\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u5982\u679c\u4e0d\u9075\u5b88\u6b64\u5047\u8bbe\u8be5\u600e\u4e48\u529e\uff1a<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e0d\u5e78\u7684\u662f\uff0c\u5982\u679c\u4e0d\u6ee1\u8db3\u8fd9\u4e2a\u5047\u8bbe\uff0c\u4f60\u5c31\u65e0\u80fd\u4e3a\u529b\u3002\u7b80\u800c\u8a00\u4e4b\uff0c\u5982\u679c\u6536\u96c6\u6570\u636e\u7684\u65b9\u5f0f\u4f7f\u5f97\u6bcf\u7ec4\u4e2d\u7684\u89c2\u5bdf\u7ed3\u679c\u4e0d\u72ec\u7acb\u4e8e\u5176\u4ed6\u7ec4\u4e2d\u7684\u89c2\u5bdf\u7ed3\u679c\uff0c\u6216\u8005\u6bcf\u7ec4\u4e2d\u7684\u89c2\u5bdf\u7ed3\u679c\u4e0d\u662f\u901a\u8fc7\u968f\u673a\u8fc7\u7a0b\u83b7\u5f97\u7684\uff0c\u5219\u65b9\u5dee\u5206\u6790\u7ed3\u679c\u5c06\u4e0d\u53ef\u9760\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u4e0d\u6ee1\u8db3\u6b64\u5047\u8bbe\uff0c\u6700\u597d\u7684\u529e\u6cd5\u662f\u4f7f\u7528\u968f\u673a\u8bbe\u8ba1\u91cd\u65b0\u521b\u5efa\u5b9e\u9a8c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u8fdb\u4e00\u6b65\u9605\u8bfb\uff1a<\/strong><\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Excel \u4e2d\u6267\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u5355\u5411\u65b9\u5dee\u5206\u6790\u662f\u4e00\u79cd\u7edf\u8ba1\u68c0\u9a8c\uff0c\u7528\u4e8e\u786e\u5b9a\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u663e\u7740\u5dee\u5f02\u3002 \u4ee5\u4e0b\u662f\u6211\u4eec\u4f55\u65f6\u53ef\u4ee5\u4f7f\u7528\u5355\u5411 [&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":[],"class_list":["post-546","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u68c0\u67e5\u65b9\u5dee\u5206\u6790\u5047\u8bbe - Statorials<\/title>\n<meta name=\"description\" content=\"\u4e00\u4e2a\u7b80\u5355\u7684\u6559\u7a0b\uff0c\u89e3\u91ca\u4e86\u65b9\u5dee\u5206\u6790\u7684\u4e09\u4e2a\u57fa\u672c\u5047\u8bbe\u4ee5\u53ca\u5982\u4f55\u9a8c\u8bc1\u8fd9\u4e9b\u5047\u8bbe\u662f\u5426\u5f97\u5230\u6ee1\u8db3\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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