{"id":1312,"date":"2023-07-26T22:05:53","date_gmt":"2023-07-26T22:05:53","guid":{"rendered":"https:\/\/statorials.org\/ja\/r-%e3%81%a6%e3%82%99%e9%87%8d%e5%9b%9e%e5%b8%b0%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/"},"modified":"2023-07-26T22:05:53","modified_gmt":"2023-07-26T22:05:53","slug":"r-%e3%81%a6%e3%82%99%e9%87%8d%e5%9b%9e%e5%b8%b0%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r-%e3%81%a6%e3%82%99%e9%87%8d%e5%9b%9e%e5%b8%b0%e3%82%92%e3%83%95%e3%82%9a%e3%83%ad%e3%83%83%e3%83%88%e3%81%99%e3%82%8b\/","title":{"rendered":"R \u3067\u91cd\u56de\u5e30\u7d50\u679c\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">R \u3067<a href=\"https:\/\/statorials.org\/ja\/r-\u3066\u3099\u306e\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener\">\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30<\/a>\u3092\u5b9f\u884c\u3059\u308b\u5834\u5408\u3001\u5358\u4e00\u306e\u4e88\u6e2c\u5909\u6570\u3068\u5358\u4e00\u306e<a href=\"https:\/\/statorials.org\/ja\/\u5909\u6570\u306e\u8aac\u660e\u5fdc\u7b54\/\" target=\"_blank\" rel=\"noopener\">\u5fdc\u7b54\u5909\u6570<\/a>\u306e\u307f\u3092\u6271\u3046\u305f\u3081\u3001\u8fd1\u4f3c\u3055\u308c\u305f\u56de\u5e30\u76f4\u7dda\u3092\u8996\u899a\u5316\u3059\u308b\u306e\u304c\u7c21\u5358\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u306b\u9069\u5408\u3055\u305b\u3001\u7d50\u679c\u3092\u30d7\u30ed\u30c3\u30c8\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;\">#create dataset\n<\/span>data &lt;- data.frame(x = c(1, 1, 2, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11),\n                   y = c(13, 14, 17, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40, 41))\n\n<span style=\"color: #008080;\">#fit simple linear regression model\n<\/span>model &lt;- lm(y ~ x, data = data)\n\n<span style=\"color: #008080;\">#create scatterplot of data\n<\/span>plot(data$x, data$y)\n\n<span style=\"color: #008080;\">#add fitted regression line\n<\/span>abline(model)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12859 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/plotmultipleregression1.png\" alt=\"\u6563\u5e03\u56f3\u3092\u4f7f\u7528\u3057\u3066 R \u3067\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u76f4\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\" width=\"413\" height=\"381\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3060\u3057\u3001<a href=\"https:\/\/statorials.org\/ja\/\u91cd\u7dda\u5f62\u56de\u5e30r\/\" target=\"_blank\" rel=\"noopener\">\u91cd\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u5834\u5408\u3001<\/a>\u8907\u6570\u306e\u4e88\u6e2c\u5909\u6570\u304c\u3042\u308a\u3001\u5358\u7d14\u306b 2D \u30b0\u30e9\u30d5\u4e0a\u306b\u56de\u5e30\u76f4\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u306a\u3044\u305f\u3081\u3001\u7d50\u679c\u3092\u8996\u899a\u5316\u3059\u308b\u3053\u3068\u304c\u56f0\u96e3\u306b\u306a\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee3\u308f\u308a\u306b\u3001<strong>\u8ffd\u52a0\u5909\u6570\u30d7\u30ed\u30c3\u30c8<\/strong>(\u300c\u504f\u56de\u5e30\u30d7\u30ed\u30c3\u30c8\u300d\u3068\u547c\u3070\u308c\u308b\u3053\u3068\u3082\u3042\u308a\u307e\u3059) \u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002\u3053\u308c\u306f<em>\u3001\u30e2\u30c7\u30eb\u5185\u306e\u4ed6\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u5b58\u5728\u3092\u5236\u5fa1\u3057\u306a\u304c\u3089\u3001\u5fdc\u7b54\u5909\u6570\u3068\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u9593\u306e<\/em>\u95a2\u4fc2\u3092\u8868\u793a\u3059\u308b\u500b\u5225\u306e\u30d7\u30ed\u30c3\u30c8\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001R \u3067\u91cd\u56de\u5e30\u3092\u5b9f\u884c\u3057\u3001\u8ffd\u52a0\u306e\u5909\u6570\u30d7\u30ed\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u7d50\u679c\u3092\u8996\u899a\u5316\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: R \u3067\u306e\u91cd\u7dda\u5f62\u56de\u5e30\u7d50\u679c\u306e\u30d7\u30ed\u30c3\u30c8<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u7d44\u307f\u8fbc\u307f\u306e<strong>mtcars<\/strong>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u3001\u6b21\u306e\u91cd\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092 R \u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u5f53\u3066\u306f\u3081\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit multiple linear regression model\n<span style=\"color: #000000;\">model &lt;- lm(mpg ~ disp + hp + drat, data = mtcars)\n<\/span>\n#view results of model\n<span style=\"color: #000000;\">summary(model)\n\nCall:\nlm(formula = mpg ~ disp + hp + drat, data = mtcars)\n\nResiduals:\n    Min 1Q Median 3Q Max \n-5.1225 -1.8454 -0.4456 1.1342 6.4958 \n\nCoefficients:\n             Estimate Std. Error t value Pr(&gt;|t|)   \n(Intercept) 19.344293 6.370882 3.036 0.00513 **\navailable -0.019232 0.009371 -2.052 0.04960 * \nhp -0.031229 0.013345 -2.340 0.02663 * \ndrat 2.714975 1.487366 1.825 0.07863 . \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 3.008 on 28 degrees of freedom\nMultiple R-squared: 0.775, Adjusted R-squared: 0.7509 \nF-statistic: 32.15 on 3 and 28 DF, p-value: 3.28e-09\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u304b\u3089\u3001\u5404\u4fc2\u6570\u306e p \u5024\u304c 0.1 \u672a\u6e80\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u308f\u304b\u308a\u3084\u3059\u304f\u3059\u308b\u305f\u3081\u306b\u3001\u5404\u4e88\u6e2c\u5909\u6570\u306f\u6709\u610f\u3067\u3042\u308a\u3001\u30e2\u30c7\u30eb\u306b\u542b\u3081\u308b\u5fc5\u8981\u304c\u3042\u308b\u3068\u4eee\u5b9a\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8ffd\u52a0\u3055\u308c\u305f\u5909\u6570\u306e\u30d7\u30ed\u30c3\u30c8\u3092\u751f\u6210\u3059\u308b\u306b\u306f\u3001 <strong>car<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u306e<strong>avPlots()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#load car package\n<span style=\"color: #000000;\">library(car)\n<\/span>\n#produce added variable plots\n<span style=\"color: #000000;\">avPlots(model)<\/span>\n<\/span><\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12861 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/ajoutevarplots1.png\" alt=\"R \u3067\u306e\u91cd\u56de\u5e30\u306e\u30d7\u30ed\u30c3\u30c8\" width=\"503\" height=\"507\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u5404\u30d7\u30ed\u30c3\u30c8\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">X \u8ef8\u306b\u306f\u5358\u4e00\u306e\u4e88\u6e2c\u5909\u6570\u304c\u8868\u793a\u3055\u308c\u3001Y \u8ef8\u306b\u306f\u5fdc\u7b54\u5909\u6570\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u9752\u3044\u7dda\u306f<em>\u3001\u4ed6\u306e\u3059\u3079\u3066\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u5024\u3092\u4e00\u5b9a\u306b\u4fdd\u3061\u306a\u304c\u3089<\/em>\u3001\u4e88\u6e2c\u5b50\u5909\u6570\u3068\u5fdc\u7b54\u5909\u6570\u306e\u9593\u306e\u95a2\u9023\u6027\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5404\u30b0\u30e9\u30d5\u5185\u306e\u30e9\u30d9\u30eb\u4ed8\u304d\u70b9\u306f\u3001\u6700\u5927\u306e<a href=\"https:\/\/statorials.org\/ja\/\u6b8b\u57fa\/\" target=\"_blank\" rel=\"noopener\">\u6b8b\u5dee\u3092<\/a>\u6301\u3064 2 \u3064\u306e<a href=\"https:\/\/statorials.org\/ja\/\u7d71\u8a08\u306b\u304a\u3051\u308b\u89b3\u5bdf\/\" target=\"_blank\" rel=\"noopener\">\u89b3\u6e2c\u5024<\/a>\u3068\u3001\u6700\u5927\u306e\u90e8\u5206\u3066\u3053\u6bd4\u3092\u6301\u3064 2 \u3064\u306e\u89b3\u6e2c\u5024\u3092\u8868\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5404\u30d7\u30ed\u30c3\u30c8\u306e\u7dda\u306e\u89d2\u5ea6\u306f\u3001\u63a8\u5b9a\u3055\u308c\u305f\u56de\u5e30\u5f0f\u306e\u4fc2\u6570\u306e\u7b26\u53f7\u306b\u5bfe\u5fdc\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3068\u3048\u3070\u3001\u30e2\u30c7\u30eb\u5185\u306e\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u63a8\u5b9a\u4fc2\u6570\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u8868\u793a:<\/strong> -0.019232<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>ch:<\/strong> -0.031229<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u65e5\u4ed8:<\/strong> 2.714975<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u8ffd\u52a0\u3055\u308c\u305f\u5909\u6570\u30d7\u30ed\u30c3\u30c8\u3067\u306f\u3001 <em>drat<\/em>\u306b\u5bfe\u3057\u3066\u7dda\u306e\u89d2\u5ea6\u304c\u6b63\u3067\u3042\u308b\u306e\u306b\u5bfe\u3057\u3001 <em>disp<\/em>\u304a\u3088\u3073<em>hp<\/em>\u306b\u5bfe\u3057\u3066\u306f\u8ca0\u3067\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u308c\u306f\u3001\u63a8\u5b9a\u3055\u308c\u305f\u4fc2\u6570\u306e\u7b26\u53f7\u306b\u5bfe\u5fdc\u3057\u307e\u3059\u3002<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12864 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/ajoutevarplots2.png\" alt=\"R \u306b\u5909\u6570\u30d7\u30ed\u30c3\u30c8\u3092\u8ffd\u52a0\u3059\u308b\" width=\"473\" height=\"495\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u8907\u6570\u306e\u4e88\u6e2c\u5909\u6570\u304c\u3042\u308b\u305f\u3081\u30012D \u30b0\u30e9\u30d5\u4e0a\u306b\u5358\u4e00\u306e\u8fd1\u4f3c\u56de\u5e30\u76f4\u7dda\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u3053\u3068\u306f\u3067\u304d\u307e\u305b\u3093\u304c\u3001\u3053\u308c\u3089\u306e\u8ffd\u52a0\u5909\u6570\u30b0\u30e9\u30d5\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u4ed6\u306e\u4e88\u6e2c\u5909\u6570\u3092\u4e00\u5b9a\u306b\u4fdd\u3061\u306a\u304c\u3089\u3001\u500b\u3005\u306e\u4e88\u6e2c\u5909\u6570\u3068\u5fdc\u7b54\u5909\u6570\u306e\u9593\u306e\u95a2\u4fc2\u3092\u89b3\u5bdf\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>R \u3067\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u5834\u5408\u3001\u5358\u4e00\u306e\u4e88\u6e2c\u5909\u6570\u3068\u5358\u4e00\u306e\u5fdc\u7b54\u5909\u6570\u306e\u307f\u3092\u6271\u3046\u305f\u3081\u3001\u8fd1\u4f3c\u3055\u308c\u305f\u56de\u5e30\u76f4\u7dda\u3092\u8996\u899a\u5316\u3059\u308b\u306e\u304c\u7c21\u5358\u3067\u3059\u3002 \u305f\u3068\u3048\u3070\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u306b\u9069\u5408\u3055\u305b\u3001\u7d50\u679c\u3092\u30d7\u30ed\u30c3\u30c8\u3059\u308b\u65b9 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-1312","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized 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