{"id":514,"date":"2023-07-29T16:03:36","date_gmt":"2023-07-29T16:03:36","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e9%85%8d%e5%af%b9%e6%a0%b7%e6%9c%ac-t-%e6%a3%80%e9%aa%8c-r\/"},"modified":"2023-07-29T16:03:36","modified_gmt":"2023-07-29T16:03:36","slug":"%e9%85%8d%e5%af%b9%e6%a0%b7%e6%9c%ac-t-%e6%a3%80%e9%aa%8c-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e9%85%8d%e5%af%b9%e6%a0%b7%e6%9c%ac-t-%e6%a3%80%e9%aa%8c-r\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u6267\u884c\u914d\u5bf9\u6837\u672c t \u68c0\u9a8c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u914d\u5bf9\u6837\u672ct\u68c0\u9a8c\/\" target=\"_blank\" rel=\"noopener\">\u914d\u5bf9\u6837\u672c t \u68c0\u9a8c<\/a>\u662f\u4e00\u79cd\u7edf\u8ba1\u68c0\u9a8c\uff0c\u5f53\u4e00\u4e2a\u6837\u672c\u7684\u6bcf\u4e2a\u89c2\u5bdf\u503c\u53ef\u4ee5\u4e0e\u53e6\u4e00\u4e2a\u6837\u672c\u7684<a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u89c2\u5bdf\/\" target=\"_blank\" rel=\"noopener\">\u89c2\u5bdf<\/a>\u503c\u76f8\u5339\u914d\u65f6\uff0c\u5b83\u4f1a\u6bd4\u8f83\u4e24\u4e2a\u6837\u672c\u7684\u5e73\u5747\u503c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u60f3\u77e5\u9053\u67d0\u4e2a\u8bfe\u7a0b\u662f\u5426\u5bf9\u5b66\u751f\u5728\u7279\u5b9a\u8003\u8bd5\u4e2d\u7684\u8868\u73b0\u6709\u91cd\u5927\u5f71\u54cd\u3002\u4e3a\u4e86\u6d4b\u8bd5\u8fd9\u4e00\u70b9\uff0c\u6211\u4eec\u8981\u6c42\u4e00\u4e2a\u73ed\u7ea7 20 \u540d\u5b66\u751f\u8fdb\u884c\u9884\u6d4b\u8bd5\u3002\u7136\u540e\uff0c\u6bcf\u4e2a\u5b66\u751f\u6bcf\u5929\u90fd\u53c2\u52a0\u5b66\u4e60\u8ba1\u5212\uff0c\u6301\u7eed\u4e24\u5468\u3002\u7136\u540e\uff0c\u5b66\u751f\u91cd\u65b0\u53c2\u52a0\u7c7b\u4f3c\u96be\u5ea6\u7684\u6d4b\u8bd5\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u6bd4\u8f83\u7b2c\u4e00\u6b21\u548c\u7b2c\u4e8c\u6b21\u6d4b\u8bd5\u7684\u5e73\u5747\u5206\u6570\u4e4b\u95f4\u7684\u5dee\u5f02\uff0c\u6211\u4eec\u4f7f\u7528\u914d\u5bf9 t \u68c0\u9a8c\uff0c\u56e0\u4e3a\u5bf9\u4e8e\u6bcf\u4e2a\u5b66\u751f\u6765\u8bf4\uff0c\u4ed6\u4eec\u5728\u7b2c\u4e00\u6b21\u6d4b\u8bd5\u4e2d\u7684\u5206\u6570\u53ef\u4ee5\u4e0e\u4ed6\u4eec\u5728\u7b2c\u4e8c\u6b21\u6d4b\u8bd5\u4e2d\u7684\u5206\u6570\u76f8\u5173\u8054\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5982\u4f55\u8fdb\u884c\u914d\u5bf9 t \u68c0\u9a8c<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u8981\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\uff1a<\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u6b65\u9aa4 1\uff1a\u9648\u8ff0\u539f\u5047\u8bbe\u548c\u5907\u62e9\u5047\u8bbe\u3002<\/span><\/strong><\/p>\n<p> <span style=\"color: #000000;\"><strong>H <sub>0<\/sub> : \u03bc <sub>d<\/sub> = 0<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>H <sub>a<\/sub> : \u03bc <sub>d<\/sub> \u2260 0<\/strong> \uff08\u4e24\u4fa7\uff09<\/span><br \/> <span style=\"color: #000000;\"><strong>H <sub>a<\/sub> : \u03bc <sub>d<\/sub> &gt; 0<\/strong> \uff08\u5355\u4fa7\uff09<\/span><br \/> <span style=\"color: #000000;\"><strong>H <sub>a<\/sub> : \u03bc <sub>d<\/sub> &lt; 0<\/strong> \uff08\u5355\u4fa7\uff09<\/span><\/p>\n<p><span style=\"color: #000000;\"><em>\u5176\u4e2d<strong>\u03bc <sub>d<\/sub><\/strong>\u662f\u5e73\u5747\u5dee\u3002<\/em><\/span><\/p>\n<p><strong><span style=\"color: #000000;\">\u6b65\u9aa4 2\uff1a\u67e5\u627e\u68c0\u9a8c\u7edf\u8ba1\u91cf\u548c\u76f8\u5e94\u7684 p \u503c\u3002<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u4ee4<em>a<\/em> = \u5b66\u751f\u5728\u7b2c\u4e00\u6b21\u6d4b\u8bd5\u4e2d\u7684\u5206\u6570\uff0c <em>b<\/em> = \u5b66\u751f\u5728\u7b2c\u4e8c\u6b21\u6d4b\u8bd5\u4e2d\u7684\u5206\u6570\u3002\u8981\u68c0\u9a8c\u6d4b\u8bd5\u5206\u6570\u4e4b\u95f4\u7684\u771f\u5b9e\u5e73\u5747\u5dee\u4e3a\u96f6\u7684\u539f\u5047\u8bbe\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u8ba1\u7b97\u6bcf\u5bf9\u5206\u6570\u4e4b\u95f4\u7684\u5dee\u5f02 (d <sub>i<\/sub> = b <sub>i<\/sub> \u2013 a <sub>i<\/sub> )<\/span><\/li>\n<li><span style=\"color: #000000;\">\u8ba1\u7b97\u5e73\u5747\u5dee (d)<\/span><\/li>\n<li><span style=\"color: #000000;\">\u8ba1\u7b97\u5dee\u5f02 s <sub>d<\/sub>\u7684\u6807\u51c6\u5dee<\/span><\/li>\n<li><span style=\"color: #000000;\">\u8ba1\u7b97 t \u7edf\u8ba1\u91cf\uff0c\u5373 T = d \/ (s <sub>d<\/sub> \/ \u221an)<\/span><\/li>\n<li><span style=\"color: #000000;\">\u627e\u5230\u81ea\u7531\u5ea6\u4e3a<em>n-1 \u7684<\/em>t \u7edf\u8ba1\u91cf\u7684\u76f8\u5e94 p \u503c\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 3\uff1a\u6839\u636e\u663e\u7740\u6027\u6c34\u5e73\u62d2\u7edd\u6216\u4e0d\u62d2\u7edd\u539f\u5047\u8bbe\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c p \u503c\u5c0f\u4e8e\u6240\u9009\u7684\u663e\u7740\u6027\u6c34\u5e73\uff0c\u6211\u4eec\u62d2\u7edd\u539f\u5047\u8bbe\u5e76\u5f97\u51fa\u7ed3\u8bba\uff1a\u4e24\u7ec4\u5747\u503c\u4e4b\u95f4\u5b58\u5728\u7edf\u8ba1\u663e\u7740\u5dee\u5f02\u3002\u5426\u5219\uff0c\u6211\u4eec\u5c06\u65e0\u6cd5\u62d2\u7edd\u539f\u5047\u8bbe\u3002<\/span><\/p>\n<h2><strong><span style=\"color: #000000;\">\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c<\/span><\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u8981\u5728 R \u4e2d\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u51fd\u6570<strong>t.test()<\/strong> \uff0c\u8bed\u6cd5\u5982\u4e0b\uff1a<\/span><\/p>\n<p style=\"text-align: center;\"> <span style=\"color: #000000;\"><strong>t.test<\/strong> \uff08x\uff0cy\uff0c\u914d\u5bf9= TRUE\uff0c\u66ff\u4ee3=\u201c\u4e24\u4fa7\u201d\uff09<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x,y\uff1a<\/strong>\u6211\u4eec\u8981\u6bd4\u8f83\u7684\u4e24\u4e2a\u6570\u5b57\u5411\u91cf<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>paired\uff1a<\/strong>\u4e00\u4e2a\u903b\u8f91\u503c\uff0c\u6307\u5b9a\u6211\u4eec\u8981\u8ba1\u7b97\u914d\u5bf9 t \u68c0\u9a8c<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u66ff\u4ee3\u65b9\u6848\uff1a<\/strong>\u66ff\u4ee3\u5047\u8bbe\u3002\u53ef\u4ee5\u8bbe\u7f6e\u4e3a\u201c\u53cc\u9762\u201d\uff08\u9ed8\u8ba4\uff09\u3001\u201c\u9876\u90e8\u201d\u6216\u201c\u5e95\u90e8\u201d\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u8bf4\u660e\u5982\u4f55\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c\uff0c\u4ee5\u786e\u5b9a 20 \u540d\u5b66\u751f\u7684\u9884\u6d4b\u8bd5\u548c\u540e\u6d4b\u8bd5\u4e4b\u95f4\u7684\u5e73\u5747\u5206\u6570\u662f\u5426\u5b58\u5728\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u521b\u5efa\u6570\u636e<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u5c06\u521b\u5efa\u6570\u636e\u96c6\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create the dataset<\/span>\ndata &lt;- data.frame(score = c(85,85, 78, 78, 92, 94, 91, 85, 72, 97,\n                             84, 95, 99, 80, 90, 88, 95, 90, 96, 89,\n                             84, 88, 88, 90, 92, 93, 91, 85, 80, 93,\n                             97, 100, 93, 91, 90, 87, 94, 83, 92, 95),\n                   group = c(rep('pre', 20), rep('post', 20)))\n\n<span style=\"color: #008080;\">#view the dataset\n<\/span>data\n\n#scoregroup\n#1 85 pre\n#2 85 pre\n#3 78 pre\n#4 78 pre\n#5 92 pre\n#6 94 pre\n#7 91 pre\n#8 85 pre\n#9 72 pre\n#10 97 pre\n#11 84 pre\n#12 95 pre\n#13 99 pre\n#14 80 pre\n#15 90 pre\n#16 88 pre\n#17 95 pre\n#18 90 pre\n#19 96 pre\n#20 89 pre\n#21 84 post\n#22 88 post\n#23 88 post\n#24 90 post\n#25 92 post\n#26 93 post\n#27 91 post\n#28 85 post\n#29 80 post\n#30 93 post\n#31 97 post\n#32 100 posts\n#33 93 post\n#34 91 post\n#35 90 post\n#36 87 post\n#37 94 post\n#38 83 post\n#39 92 post\n#40 95 post\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u53ef\u89c6\u5316\u5dee\u5f02<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528<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\"><strong>dplyr<\/strong><\/a>\u5e93\u4e2d\u7684<strong>group_by()<\/strong>\u548c<strong>summary<\/strong> <strong>()<\/strong>\u51fd\u6570\u67e5\u770b\u4e24\u4e2a\u7ec4\u7684\u6c47\u603b\u7edf\u8ba1\u4fe1\u606f\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load <em>dplyr<\/em> library\n<span style=\"color: #000000;\">library(dplyr)<\/span>\n\n#find sample size, mean, and standard deviation for each group\n<span style=\"color: #000000;\">data %&gt;%\n<span style=\"color: #800080;\">group_by<\/span> (group) %&gt;%\n  <span style=\"color: #800080;\">summarize<\/span> (\n    count = n(),\n    mean = mean(score),\n    sd = sd(score)\n  )\n<\/span><\/span>\n# A tibble: 2 x 4\n# group count mean sd\n#     \n#1 post 20 90.3 4.88\n#2 pre 20 88.2 7.24<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528 R \u4e2d\u7684<strong>boxplot()<\/strong>\u51fd\u6570\u521b\u5efa<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\">\u7bb1\u7ebf\u56fe<\/a>\u6765\u663e\u793a\u524d\u7ec4\u548c\u540e\u7ec4\u7684\u5206\u6570\u5206\u5e03\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #800080;\">boxplot<\/span> (score~group,\n  data=data,\n  main=\"Test Scores by Group\",\n  xlab=\"Group\",\n  ylab=\"Score\",\n  col=\"steelblue\",\n  border=\"black\"\n)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u6c47\u603b\u7edf\u8ba1\u6570\u636e\u548c\u7bb1\u7ebf\u56fe\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230<em>\u540e<\/em>\u7ec4\u7684\u5e73\u5747\u5f97\u5206\u7565\u9ad8\u4e8e<em>\u524d<\/em>\u7ec4\u7684\u5e73\u5747\u5f97\u5206\u3002\u6211\u4eec\u8fd8\u53ef\u4ee5\u770b\u5230\uff0c\u7ec4<em>\u540e<\/em>\u5206\u6570\u7684\u53d8\u5f02\u6027\u6bd4\u7ec4<em>\u524d<\/em>\u5206\u6570\u8981\u5c0f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u786e\u5b9a\u8fd9\u4e24\u7ec4\u5747\u503c\u4e4b\u95f4\u7684\u5dee\u5f02\u662f\u5426\u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u914d\u5bf9 t \u68c0\u9a8c\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u5728\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c\u4e4b\u524d\uff0c\u6211\u4eec\u9700\u8981\u9a8c\u8bc1\u5dee\u5f02\u7684\u5206\u5e03\u662f\u5426\u4e3a\u6b63\u6001\uff08\u6216\u8fd1\u4f3c\u6b63\u6001\uff09\u5206\u5e03\u3002\u4e3a\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u65b0\u5411\u91cf\uff0c\u5b9a\u4e49\u4e3a\u524d\u540e\u5206\u6570\u4e4b\u95f4\u7684\u5dee\u5f02\uff0c\u5e76\u5bf9\u8fd9\u4e2a\u503c\u5411\u91cf\u6267\u884c Shapiro-Wilk \u68c0\u9a8c\u4ee5\u9a8c\u8bc1\u6b63\u6001\u6027\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define new vector for difference between post and pre scores\n<\/span>differences &lt;- with(data, score[group == \"post\"] - score[group == \"pre\"])\n\n<span style=\"color: #008080;\">#perform shapiro-wilk test for normality on this vector of values\n<\/span>shapiro.test(differences)\n\n# Shapiro-Wilk normality test\n#\n#data: differences\n#W = 0.92307, p-value = 0.1135\n#<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u68c0\u9a8c\u7684 p \u503c\u4e3a 0.1135\uff0c\u5927\u4e8e alpha = 0.05\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u65e0\u6cd5\u62d2\u7edd\u6570\u636e\u5448\u6b63\u6001\u5206\u5e03\u7684\u539f\u5047\u8bbe\u3002\u8fd9\u610f\u5473\u7740\u6211\u4eec\u73b0\u5728\u53ef\u4ee5\u7ee7\u7eed\u8fdb\u884c\u914d\u5bf9 t \u68c0\u9a8c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6765\u6267\u884c\u914d\u5bf9 t \u68c0\u9a8c\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #800080;\">t.test<\/span> (score~group, data = data, paired = TRUE)\n\n# Paired t-test\n#\n#data: score by group\n#t = 1.588, df = 19, p-value = 0.1288\n#alternative hypothesis: true difference in means is not equal to 0\n#95 percent confidence interval:\n# -0.6837307 4.9837307\n#sample estimates:\n#mean of the differences \n#2.15 \n<\/strong><\/span><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>t<\/strong>\u68c0\u9a8c\u7edf\u8ba1\u91cf\u4e3a<strong>1.588<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6b64\u5177\u6709 19 \u4e2a\u81ea\u7531\u5ea6 (df) \u7684\u68c0\u9a8c\u7edf\u8ba1\u91cf\u7684 p \u503c\u4e3a<strong>0.1288<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5747\u503c\u5dee\u7684 95% \u7f6e\u4fe1\u533a\u95f4\u4e3a<strong>(-0.6837, 4.9837)<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u524d\u540e\u7ec4\u7684\u5e73\u5747\u5206\u6570\u5dee\u4e3a<strong>2.15<\/strong> \u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u56e0\u6b64\uff0c\u7531\u4e8e\u6211\u4eec\u7684 p \u503c\u4f4e\u4e8e\u663e\u7740\u6027\u6c34\u5e73 0.05\uff0c\u56e0\u6b64\u6211\u4eec\u5c06\u65e0\u6cd5\u62d2\u7edd\u4e24\u7ec4\u5747\u503c\u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u7684\u539f\u5047\u8bbe\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6362\u53e5\u8bdd\u8bf4\uff0c\u6211\u4eec\u6ca1\u6709\u8db3\u591f\u7684\u8bc1\u636e\u8868\u660e\u524d\u7ec4\u548c\u540e\u7ec4\u4e4b\u95f4\u7684\u5e73\u5747\u5206\u6570\u5728\u7edf\u8ba1\u4e0a\u5b58\u5728\u5dee\u5f02\u3002\u8fd9\u610f\u5473\u7740\u8bfe\u7a0b\u5bf9\u8003\u8bd5\u6210\u7ee9\u6ca1\u6709\u663e\u7740\u5f71\u54cd\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b64\u5916\uff0c\u6211\u4eec\u7684 95% \u7f6e\u4fe1\u533a\u95f4\u8868\u660e\u6211\u4eec\u201c95% \u786e\u4fe1\u201d\u4e24\u7ec4\u4e4b\u95f4\u7684\u771f\u5b9e\u5e73\u5747\u5dee\u5f02\u5728<strong>-0.6837<\/strong>\u548c<strong>4.9837<\/strong>\u4e4b\u95f4\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u503c<em>\u96f6<\/em>\u5305\u542b\u5728\u8be5\u7f6e\u4fe1\u533a\u95f4\u5185\uff0c\u8fd9\u610f\u5473\u7740<em>\u96f6<\/em>\u5b9e\u9645\u4e0a\u53ef\u80fd\u662f\u5e73\u5747\u5206\u6570\u4e4b\u95f4\u7684\u771f\u5b9e\u5dee\u5f02\uff0c\u8fd9\u5c31\u662f\u6211\u4eec\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\u672a\u80fd\u62d2\u7edd\u539f\u5047\u8bbe\u7684\u539f\u56e0\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u914d\u5bf9\u6837\u672c t \u68c0\u9a8c\u662f\u4e00\u79cd\u7edf\u8ba1\u68c0\u9a8c\uff0c\u5f53\u4e00\u4e2a\u6837\u672c\u7684\u6bcf\u4e2a\u89c2\u5bdf\u503c\u53ef\u4ee5\u4e0e\u53e6\u4e00\u4e2a\u6837\u672c\u7684\u89c2\u5bdf\u503c\u76f8\u5339\u914d\u65f6\uff0c\u5b83\u4f1a\u6bd4\u8f83\u4e24\u4e2a\u6837\u672c\u7684\u5e73 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