{"id":914,"date":"2023-07-28T08:02:55","date_gmt":"2023-07-28T08:02:55","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e5%a4%96%e3%82%8c%e5%80%a4%e3%82%92%e9%99%a4%e5%8e%bb%e3%81%99%e3%82%8b-r\/"},"modified":"2023-07-28T08:02:55","modified_gmt":"2023-07-28T08:02:55","slug":"%e5%a4%96%e3%82%8c%e5%80%a4%e3%82%92%e9%99%a4%e5%8e%bb%e3%81%99%e3%82%8b-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e5%a4%96%e3%82%8c%e5%80%a4%e3%82%92%e9%99%a4%e5%8e%bb%e3%81%99%e3%82%8b-r\/","title":{"rendered":"R \u3067\u5916\u308c\u5024\u3092\u524a\u9664\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u5916\u308c\u5024<\/strong>\u3068\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306e\u4ed6\u306e\u5024\u304b\u3089\u7570\u5e38\u306b\u96e2\u308c\u3066\u3044\u308b\u89b3\u6e2c\u5024\u3067\u3059\u3002\u5916\u308c\u5024\u306f\u5206\u6790\u7d50\u679c\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u305f\u3081\u3001\u554f\u984c\u3068\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u5916\u308c\u5024\u3092\u7279\u5b9a\u3057\u3066\u524a\u9664\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>R \u3067\u5916\u308c\u5024\u3092\u7279\u5b9a\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5916\u308c\u5024\u3092\u524a\u9664\u3059\u308b\u524d\u306b\u3001\u307e\u305a\u4f55\u3092\u5916\u308c\u5024\u3068\u307f\u306a\u3059\u304b\u3092\u6c7a\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u3092\u884c\u3046\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u4e00\u822c\u7684\u306a\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u56db\u5206\u4f4d\u7bc4\u56f2\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u56db\u5206\u4f4d\u7bc4\u56f2 (IQR) \u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306e 75 \u30d1\u30fc\u30bb\u30f3\u30bf\u30a4\u30eb (Q3) \u3068 25 \u30d1\u30fc\u30bb\u30f3\u30bf\u30a4\u30eb (Q1) \u306e\u5dee\u3067\u3059\u3002\u5024\u306e\u5e73\u5747 50% \u306e\u5206\u5e03\u3092\u6e2c\u5b9a\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u89b3\u6e2c\u5024\u304c\u7b2c 3 \u56db\u5206\u4f4d (Q3) \u3088\u308a\u4e0a\u306e\u56db\u5206\u4f4d\u7bc4\u56f2\u306e 1.5 \u500d\u3001\u307e\u305f\u306f\u7b2c 1 \u56db\u5206\u4f4d (Q1) \u3088\u308a\u4e0b\u306e\u56db\u5206\u4f4d\u7bc4\u56f2\u306e 1.5 \u500d\u3067\u3042\u308b\u5834\u5408\u3001\u305d\u306e\u89b3\u6e2c\u5024\u3092\u5916\u308c\u5024\u3068\u3057\u3066\u5b9a\u7fa9\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u5916\u308c\u5024 = \u89b3\u6e2c\u5024 &gt; Q3 + 1.5*IQR \u307e\u305f\u306f &lt; Q1 \u2013 1.5*IQR<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. Z \u30b9\u30b3\u30a2\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/zr\u30b9\u30b3\u30a2\/\" target=\"_blank\" rel=\"noopener noreferrer\">Z \u30b9\u30b3\u30a2\u306f\u3001<\/a>\u6307\u5b9a\u3055\u308c\u305f\u5024\u304c\u5e73\u5747\u304b\u3089\u3069\u308c\u3060\u3051\u6a19\u6e96\u504f\u5dee\u304c\u3042\u308b\u304b\u3092\u793a\u3057\u307e\u3059\u3002\u6b21\u306e\u5f0f\u3092\u4f7f\u7528\u3057\u3066 Z \u30b9\u30b3\u30a2\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>z<\/strong> = (X \u2013 \u03bc) \/ \u03c3<\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">X \u306f\u5358\u4e00\u306e\u751f\u30c7\u30fc\u30bf\u5024\u3067\u3059<\/span><\/li>\n<li><span style=\"color: #000000;\">\u03bc \u306f\u6bcd\u5e73\u5747\u3067\u3059<\/span><\/li>\n<li><span style=\"color: #000000;\">\u03c3 \u306f\u6bcd\u96c6\u56e3\u306e\u6a19\u6e96\u504f\u5dee\u3067\u3059<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">Z \u30b9\u30b3\u30a2\u304c -3 \u672a\u6e80\u307e\u305f\u306f 3 \u3088\u308a\u5927\u304d\u3044\u5834\u5408\u3001\u89b3\u6e2c\u5024\u3092\u5916\u308c\u5024\u3068\u3057\u3066\u5b9a\u7fa9\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u5916\u308c\u5024 = Z \u30b9\u30b3\u30a2\u304c 3 \u3092\u8d85\u3048\u308b\u3001\u307e\u305f\u306f -3 \u672a\u6e80\u306e\u89b3\u6e2c\u5024<\/strong><\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>R \u3067\u5916\u308c\u5024\u3092\u524a\u9664\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4f55\u304c\u5916\u308c\u5024\u3067\u3042\u308b\u3068\u8003\u3048\u308b\u304b\u3092\u6c7a\u5b9a\u3057\u305f\u3089\u3001\u305d\u308c\u3089\u3092\u7279\u5b9a\u3057\u3066\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304b\u3089\u524a\u9664\u3067\u304d\u307e\u3059\u3002\u3053\u308c\u3092\u884c\u3046\u65b9\u6cd5\u3092\u8aac\u660e\u3059\u308b\u305f\u3081\u306b\u3001\u6b21\u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible<\/span> \nset.seed(0)\n\n<span style=\"color: #008080;\">#create data frame with three columns A', 'B', 'C'<\/span> \ndf &lt;- data.frame(A=rnorm(1000, mean=10, sd=3),\n                 B=rnorm(1000, mean=20, sd=3),\n                 C=rnorm(1000, mean=30, sd=3))\n\n<span style=\"color: #008080;\">#view first six rows of data frame<\/span>\nhead(df)\n         ABC\n1 13.78886 19.13945 31.33304\n2 9.02130 25.52332 30.03579\n3 13.98940 19.52971 29.97216\n4 13.81729 15.83059 29.09287\n5 11.24392 15.58069 31.47707\n6 5.38015 19.79144 28.19184\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6b21\u306b\u3001Z \u30b9\u30b3\u30a2\u6cd5\u307e\u305f\u306f\u56db\u5206\u4f4d\u7bc4\u56f2\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u5916\u308c\u5024\u3092\u5b9a\u7fa9\u3057\u3001\u524a\u9664\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>Z\u30b9\u30b3\u30a2\u6cd5:<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u5404\u5217\u306e\u5404\u5024\u306e Z \u30b9\u30b3\u30a2\u3092\u8a08\u7b97\u3057\u3001\u7d76\u5bfe\u5024\u304c 3 \u3088\u308a\u5927\u304d\u3044 Z \u30b9\u30b3\u30a2\u3092\u5c11\u306a\u304f\u3068\u3082 1 \u3064\u6301\u3064\u884c\u3092\u524a\u9664\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;\">#find absolute value of z-score for each value in each column<\/span>\nz_scores &lt;- <span style=\"color: #3366ff;\">as.data.frame<\/span> (sapply(df, function(df) (abs(df-mean(df))\/sd(df))))\n\n<span style=\"color: #008080;\">#view first six rows of z_scores data frame\n<\/span>head(z_scores)\n\n          ABC\n1 1.2813403 0.25350805 0.39419878\n2 0.3110243 1.80496734 0.05890232\n3 1.3483190 0.12766847 0.08112630\n4 1.2908343 1.32044506 0.38824414\n5 0.4313316 1.40102642 0.44450451\n6 1.5271674 0.04327186 0.70295309\n\n<span style=\"color: #008080;\">#only keep rows in dataframe with all z-scores less than absolute value of 3<\/span> \nno_outliers &lt;- z_scores[!rowSums(z_scores&gt;3), ]\n\n<span style=\"color: #008080;\">#view row and column count of new data frame<\/span>\ndim(no_outliers)\n\n[1] 994 3\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5143\u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306b\u306f 1000 \u884c\u3068 3 \u5217\u304c\u3042\u308a\u307e\u3057\u305f\u3002\u65b0\u3057\u3044\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306b\u306f 994 \u884c\u3068 3 \u5217\u304c\u3042\u308a\u3001\u3044\u305a\u308c\u304b\u306e\u5217\u306b\u7d76\u5bfe\u5024\u304c 3 \u3088\u308a\u5927\u304d\u3044 Z \u30b9\u30b3\u30a2\u304c\u5c11\u306a\u304f\u3068\u3082 1 \u3064\u542b\u307e\u308c\u3066\u3044\u305f\u305f\u3081\u30016 \u884c\u304c\u524a\u9664\u3055\u308c\u305f\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u56db\u5206\u4f4d\u7bc4\u56f2\u6cd5:<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u5834\u5408\u306b\u3088\u3063\u3066\u306f\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u5217\u5185\u306e\u5916\u308c\u5024\u306e\u307f\u3092\u7279\u5b9a\u3057\u305f\u3044\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306e\u5217 &#8220;A&#8221; \u306b\u3042\u308b\u5916\u308c\u5024\u306e\u3042\u308b\u884c\u306e\u307f\u3092\u524a\u9664\u3057\u305f\u3044\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5217 &#8220;A&#8221; \u306e\u5024\u304c\u7b2c 3 \u56db\u5206\u4f4d (Q3) \u3088\u308a\u4e0a\u306e\u56db\u5206\u4f4d\u7bc4\u56f2\u306e 1.5 \u500d\u3001\u307e\u305f\u306f\u7b2c 1 \u56db\u5206\u4f4d\u3088\u308a\u4e0b\u306e\u56db\u5206\u4f4d\u7bc4\u56f2 (Q1) \u306e 1.5 \u500d\u3067\u3042\u308b\u884c\u3092\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u304b\u3089\u524a\u9664\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002 \u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find Q1, Q3, and interquartile range for values in column A<\/span>\nQ1 &lt;- quantile(df$A, .25)\nQ3 &lt;- quantile(df$A, .75)\nIQR &lt;- IQR(df$A)\n\n<span style=\"color: #008080;\">#only keep rows in dataframe that have values within 1.5*IQR of Q1 and Q3<\/span>\nno_outliers &lt;- subset(df, df$A&gt; (Q1 - 1.5*IQR) &amp; df$A&lt; (Q3 + 1.5*IQR))\n\n<span style=\"color: #008080;\">#view row and column count of new data frame\n<\/span>dim(no_outliers) \n\n[1] 994 3<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5143\u306e\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306b\u306f 1000 \u884c\u3068 3 \u5217\u304c\u3042\u308a\u307e\u3057\u305f\u3002\u65b0\u3057\u3044\u30c7\u30fc\u30bf \u30d5\u30ec\u30fc\u30e0\u306b\u306f 994 \u884c\u3068 3 \u5217\u304c\u3042\u308a\u3001\u5217 A \u306b\u5c11\u306a\u304f\u3068\u3082 1 \u3064\u306e\u5916\u308c\u5024\u304c\u542b\u307e\u308c\u3066\u3044\u305f\u305f\u3081\u306b 6 \u884c\u304c\u524a\u9664\u3055\u308c\u305f\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<h3><strong>\u5916\u308c\u5024\u3092\u524a\u9664\u3059\u308b\u5834\u5408<\/strong><\/h3>\n<p><span style=\"color: #000000;\">1 \u3064\u4ee5\u4e0a\u306e\u5916\u308c\u5024\u304c\u5b58\u5728\u3059\u308b\u5834\u5408\u306f\u3001\u307e\u305a\u3001\u305d\u308c\u3089\u304c\u30c7\u30fc\u30bf\u5165\u529b\u30a8\u30e9\u30fc\u306e\u7d50\u679c\u3067\u306f\u306a\u3044\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u3059\u308b\u3068\u304d\u306b\u3001\u5358\u7d14\u306b\u9593\u9055\u3063\u305f\u30c7\u30fc\u30bf\u5024\u3092\u5165\u529b\u3057\u3066\u3057\u307e\u3046\u3053\u3068\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5916\u308c\u5024\u304c\u30c7\u30fc\u30bf\u5165\u529b\u30a8\u30e9\u30fc\u306e\u7d50\u679c\u3067\u3042\u308b\u3053\u3068\u304c\u5224\u660e\u3057\u305f\u5834\u5408\u306f\u3001\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u306e<a href=\"https:\/\/statorials.org\/ja\/\u4e2d\u5fc3\u50be\u5411\u3092\u6e2c\u5b9a\u3059\u308b\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5e73\u5747\u3084\u4e2d\u592e\u5024<\/a>\u306a\u3069\u306e\u65b0\u3057\u3044\u5024\u3092\u5272\u308a\u5f53\u3066\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5024\u304c\u672c\u5f53\u306b\u5916\u308c\u5024\u3067\u3042\u308a\u3001\u5206\u6790\u5168\u4f53\u306b\u91cd\u5927\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u5834\u5408\u306f\u3001\u305d\u306e\u5024\u3092\u524a\u9664\u3059\u308b\u3053\u3068\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002\u6700\u7d42\u30ec\u30dd\u30fc\u30c8\u307e\u305f\u306f\u5206\u6790\u3067\u306f\u3001\u5916\u308c\u5024\u3092\u524a\u9664\u3057\u305f\u3053\u3068\u3092\u5fc5\u305a\u660e\u8a18\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><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001 <strong>rnorm()<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u3001\u30d9\u30af\u30c8\u30eb\u9577<em>n<\/em> \u3001\u6bcd\u5e73\u5747<em>\u03bc<\/em> 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href=\"https:\/\/statorials.org\/ja\/rapply-sapply\u3068tapply\u3092\u9069\u7528\u3059\u308b\u305f\u3081\u306e\u30ab\u3099\u30a4\u30c8\u3099\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u3001\u3053\u3061\u3089\u3092<\/a>\u3054\u89a7\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u5916\u308c\u5024\u3068\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306e\u4ed6\u306e\u5024\u304b\u3089\u7570\u5e38\u306b\u96e2\u308c\u3066\u3044\u308b\u89b3\u6e2c\u5024\u3067\u3059\u3002\u5916\u308c\u5024\u306f\u5206\u6790\u7d50\u679c\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u53ef\u80fd\u6027\u304c\u3042\u308b\u305f\u3081\u3001\u554f\u984c\u3068\u306a\u308b\u5834\u5408\u304c\u3042\u308a\u307e\u3059\u3002 \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u5916\u308c\u5024\u3092\u7279\u5b9a\u3057\u3066\u524a\u9664\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002 R  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