{"id":543,"date":"2023-07-29T13:35:37","date_gmt":"2023-07-29T13:35:37","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%82%bf%e3%82%99%e3%83%8e%e3%83%8f%e3%82%99%e4%bb%ae%e8%aa%ac\/"},"modified":"2023-07-29T13:35:37","modified_gmt":"2023-07-29T13:35:37","slug":"%e3%82%bf%e3%82%99%e3%83%8e%e3%83%8f%e3%82%99%e4%bb%ae%e8%aa%ac","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%82%bf%e3%82%99%e3%83%8e%e3%83%8f%e3%82%99%e4%bb%ae%e8%aa%ac\/","title":{"rendered":"Anova \u306e\u4eee\u5b9a\u3092\u78ba\u8a8d\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u4e00\u65b9\u5411\u5206\u6563\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001<\/a> 3 \u3064\u4ee5\u4e0a\u306e\u72ec\u7acb\u3057\u305f\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u5024\u9593\u306b\u6709\u610f\u5dee\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u308b\u7d71\u8a08\u691c\u5b9a\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u306e\u4f8b\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<blockquote>\n<p> <span style=\"color: #000000;\">90 \u4eba\u306e\u751f\u5f92\u304b\u3089\u306a\u308b\u30af\u30e9\u30b9\u3092 30 \u4eba\u305a\u3064\u306e 3 \u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u30e9\u30f3\u30c0\u30e0\u306b\u5206\u5272\u3057\u307e\u3059\u3002\u5404\u30b0\u30eb\u30fc\u30d7\u306f\u30011 \u304b\u6708\u9593\u7570\u306a\u308b\u5b66\u7fd2\u30c6\u30af\u30cb\u30c3\u30af\u3092\u4f7f\u7528\u3057\u3066\u8a66\u9a13\u306b\u5099\u3048\u307e\u3059\u3002\u6708\u672b\u306b\u3001\u751f\u5f92\u5168\u54e1\u304c\u540c\u3058\u8a66\u9a13\u3092\u53d7\u3051\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u52c9\u5f37\u6cd5\u304c\u8a66\u9a13\u306e\u6210\u7e3e\u306b\u5f71\u97ff\u3059\u308b\u304b\u3069\u3046\u304b\u77e5\u308a\u305f\u3044\u3002\u305d\u3053\u3067\u3001<strong>\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790<\/strong>\u3092\u5b9f\u884c\u3057\u3066\u30013 \u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u5e73\u5747\u30b9\u30b3\u30a2\u9593\u306b\u7d71\u8a08\u7684\u306b\u6709\u610f\u306a\u5dee\u304c\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u5224\u65ad\u3057\u307e\u3059\u3002<\/span><\/p>\n<\/blockquote>\n<p><span style=\"color: #000000;\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3059\u308b\u524d\u306b\u3001\u307e\u305a 3 \u3064\u306e\u4eee\u5b9a\u304c\u6e80\u305f\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u6b63\u898f\u6027<\/strong>\u2013 \u5404\u30b5\u30f3\u30d7\u30eb\u306f\u6b63\u898f\u5206\u5e03\u3057\u305f\u6bcd\u96c6\u56e3\u304b\u3089\u62bd\u51fa\u3055\u308c\u307e\u3057\u305f\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \u7b49\u3057\u3044\u5206\u6563<\/strong>\u2013 \u30b5\u30f3\u30d7\u30eb\u304c\u62bd\u51fa\u3055\u308c\u305f\u6bcd\u96c6\u56e3\u306e\u5206\u6563\u306f\u7b49\u3057\u3044\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. \u72ec\u7acb\u6027<\/strong>\u2013 \u5404\u30b0\u30eb\u30fc\u30d7\u5185\u306e\u89b3\u6e2c\u5024\u306f\u4e92\u3044\u306b\u72ec\u7acb\u3057\u3066\u304a\u308a\u3001\u30b0\u30eb\u30fc\u30d7\u5185\u306e\u89b3\u6e2c\u5024\u306f<\/span><span style=\"color: #000000;\">\u30e9\u30f3\u30c0\u30e0\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u306b\u3088\u3063\u3066\u53d6\u5f97\u3055\u308c\u307e\u3057\u305f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089\u306e\u4eee\u5b9a\u304c\u6e80\u305f\u3055\u308c\u306a\u3044\u5834\u5408\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306e\u7d50\u679c\u306f\u4fe1\u983c\u3067\u304d\u306a\u3044\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u3053\u308c\u3089\u306e\u524d\u63d0\u3092\u78ba\u8a8d\u3059\u308b\u65b9\u6cd5\u3068\u3001\u3053\u308c\u3089\u306e\u524d\u63d0\u306b\u9055\u53cd\u3057\u3066\u3044\u308b\u5834\u5408\u306e\u5bfe\u51e6\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4eee\u5b9a #1: \u6b63\u5e38\u6027<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">ANOVA \u306f\u3001\u5404\u30b5\u30f3\u30d7\u30eb\u304c\u6b63\u898f\u5206\u5e03\u3057\u305f\u6bcd\u96c6\u56e3\u304b\u3089\u62bd\u51fa\u3055\u308c\u305f\u3053\u3068\u3092\u524d\u63d0\u3068\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">R \u3067\u3053\u306e\u4eee\u8aac\u3092\u78ba\u8a8d\u3059\u308b\u65b9\u6cd5:<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3059\u308b\u306b\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u307e\u305f\u306f<a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">QQ \u30d7\u30ed\u30c3\u30c8\u3092<\/a>\u4f7f\u7528\u3057\u3066\u4eee\u8aac\u3092\u8996\u899a\u7684\u306b\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">Shapiro-Wilk\u3001Kolmogorov-Smironov\u3001Jarque-Barre\u3001D&#8217;Agostino-Pearson \u306a\u3069\u306e\u6b63\u5f0f\u306a\u7d71\u8a08\u691c\u5b9a\u3092\u4f7f\u7528\u3057\u3066\u4eee\u8aac\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u305f\u3068\u3048\u3070\u3001\u6e1b\u91cf\u5b9f\u9a13\u306b\u53c2\u52a0\u3059\u308b\u4eba\u3092 90 \u4eba\u52df\u96c6\u3057\u300130 \u4eba\u3092\u30e9\u30f3\u30c0\u30e0\u306b\u5272\u308a\u5f53\u3066\u3066\u3001\u30d7\u30ed\u30b0\u30e9\u30e0 A\u3001\u30d7\u30ed\u30b0\u30e9\u30e0 B\u3001\u307e\u305f\u306f\u30d7\u30ed\u30b0\u30e9\u30e0 C \u306e\u3044\u305a\u308c\u304b\u3092 1 \u304b\u6708\u9593\u5b9f\u884c\u3059\u308b\u3068\u3057\u307e\u3059\u3002\u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u6e1b\u91cf\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u304b\u3069\u3046\u304b\u3092\u78ba\u8a8d\u3059\u308b\u305f\u3081\u306b\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3001QQ \u30d7\u30ed\u30c3\u30c8\u3001\u304a\u3088\u3073 Shapiro-Wilk \u691c\u5b9a\u3092\u4f7f\u7528\u3057\u3066\u6b63\u898f\u6027\u306e\u4eee\u5b9a\u3092\u30c1\u30a7\u30c3\u30af\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. ANOVA \u30e2\u30c7\u30eb\u3092\u5f53\u3066\u306f\u3081\u307e\u3059\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. \u5fdc\u7b54\u5024\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/strong><\/span> <\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create histogram<\/span>\nhist(data$weight_loss)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-4758 size-full\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/histogramme.jpg\" alt=\"\" width=\"541\" height=\"392\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u5206\u5e03\u306f\u3042\u307e\u308a\u6b63\u898f\u5206\u5e03\u3067\u306f\u3042\u308a\u307e\u305b\u3093 (\u305f\u3068\u3048\u3070\u3001\u300c\u91e3\u9418\u300d\u306e\u5f62\u3067\u306f\u3042\u308a\u307e\u305b\u3093) \u304c\u3001QQ \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3066\u5206\u5e03\u3092\u3082\u3046\u4e00\u5ea6\u78ba\u8a8d\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3. \u6b8b\u5dee\u306e QQ \u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create QQ plot to compare this dataset to a theoretical normal distribution<\/span>\nqqnorm(model$residuals)\n\n<span style=\"color: #008080;\">#add straight diagonal line to plot\n<\/span>qqline(model$residuals)<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-4760 size-full\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/qqplot.jpg\" alt=\"R \u3067\u306e Q-Q \u30d7\u30ed\u30c3\u30c8\u306e\u4f8b\" width=\"557\" height=\"394\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u306b\u3001\u30c7\u30fc\u30bf \u30dd\u30a4\u30f3\u30c8\u304c QQ \u30d7\u30ed\u30c3\u30c8\u306e\u76f4\u7dda\u306e\u5bfe\u89d2\u7dda\u306b\u6cbf\u3063\u3066\u914d\u7f6e\u3055\u308c\u3066\u3044\u308b\u5834\u5408\u3001\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u306f\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3046\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001\u7aef\u306b\u6cbf\u3063\u305f\u7dda\u304b\u3089\u9855\u8457\u306a\u9038\u8131\u304c\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u30c7\u30fc\u30bf\u304c\u6b63\u898f\u5206\u5e03\u3057\u3066\u3044\u306a\u3044\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>4. \u6b63\u898f\u6027\u306b\u3064\u3044\u3066 Shapiro-Wilk \u691c\u5b9a\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#Conduct Shapiro-Wilk Test for normality<\/span>\nshapiro. <span style=\"color: #3366ff;\">test<\/span> (data$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 \u691c\u5b9a\u3067\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u304c\u6b63\u898f\u5206\u5e03\u306b\u7531\u6765\u3057\u306a\u3044\u3068\u3044\u3046\u5bfe\u7acb\u4eee\u8aac\u306b\u5bfe\u3057\u3066\u3001\u30b5\u30f3\u30d7\u30eb\u304c\u6b63\u898f\u5206\u5e03\u306b\u7531\u6765\u3059\u308b\u3068\u3044\u3046\u5e30\u7121\u4eee\u8aac\u3092\u691c\u5b9a\u3057\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001\u691c\u5b9a\u306e p \u5024\u306f<strong>0.005999<\/strong>\u3067\u3001\u30a2\u30eb\u30d5\u30a1 \u30ec\u30d9\u30eb\u306e 0.05 \u3088\u308a\u3082\u4f4e\u304f\u306a\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u304c\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3063\u3066\u3044\u306a\u3044\u3053\u3068\u3092\u793a\u5506\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u3053\u306e\u524d\u63d0\u304c\u5c0a\u91cd\u3055\u308c\u306a\u3044\u5834\u5408\u306f\u3069\u3046\u3059\u308c\u3070\u3088\u3044\u3067\u3059\u304b:<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u306b\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001\u30b5\u30f3\u30d7\u30eb \u30b5\u30a4\u30ba\u304c\u5341\u5206\u306b\u5927\u304d\u3044\u9650\u308a\u3001\u6b63\u898f\u6027\u306e\u4eee\u5b9a\u306e\u9055\u53cd\u306b\u5bfe\u3057\u3066\u975e\u5e38\u306b\u5805\u7262\u3067\u3042\u308b\u3068\u8003\u3048\u3089\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3055\u3089\u306b\u3001\u30b5\u30f3\u30d7\u30eb\u304c\u975e\u5e38\u306b\u5927\u304d\u3044\u5834\u5408\u3001\u30b7\u30e3\u30d4\u30ed\u30fb\u30a6\u30a3\u30eb\u30af\u691c\u5b9a\u306a\u3069\u306e\u7d71\u8a08\u691c\u5b9a\u3067\u306f\u3001\u307b\u3068\u3093\u3069\u306e\u5834\u5408\u3001\u30c7\u30fc\u30bf\u304c\u6b63\u898f\u3067\u306f\u306a\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3053\u306e\u305f\u3081\u3001\u591a\u304f\u306e\u5834\u5408\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3084 QQ \u30d7\u30ed\u30c3\u30c8\u306a\u3069\u306e\u30b0\u30e9\u30d5\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30fc\u30bf\u3092\u8996\u899a\u7684\u306b\u691c\u67fb\u3059\u308b\u3053\u3068\u304c\u6700\u5584\u3067\u3059\u3002\u30b0\u30e9\u30d5\u3092\u898b\u308b\u3060\u3051\u3067\u3001\u30c7\u30fc\u30bf\u304c\u6b63\u898f\u5206\u5e03\u3057\u3066\u3044\u308b\u304b\u3069\u3046\u304b\u3092\u304b\u306a\u308a\u7406\u89e3\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b63\u898f\u6027\u306e\u524d\u63d0\u304c<em>\u8457\u3057\u304f<\/em>\u9055\u53cd\u3055\u308c\u3066\u3044\u308b\u5834\u5408\u3001\u307e\u305f\u306f\u5358\u306b\u975e\u5e38\u306b\u4fdd\u5b88\u7684\u3067\u3042\u308a\u305f\u3044\u5834\u5408\u306b\u306f\u30012 \u3064\u306e\u9078\u629e\u80a2\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>(1)<\/strong>\u5206\u5e03\u304c\u3088\u308a\u6b63\u898f\u5206\u5e03\u306b\u306a\u308b\u3088\u3046\u306b\u30c7\u30fc\u30bf\u306e\u5fdc\u7b54\u5024\u3092\u5909\u63db\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>(2)<\/strong>\u6b63\u898f\u6027\u306e\u4eee\u5b9a\u3092\u5fc5\u8981\u3068\u3057\u306a\u3044<a href=\"https:\/\/statorials.org\/ja\/\u30af\u30e9\u30b9\u30ab\u30eb\u30fb\u30a6\u30a9\u30ea\u30b9\u30fb\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener\">\u30af\u30e9\u30b9\u30ab\u30eb\u30fb\u30a6\u30a9\u30ea\u30b9\u691c\u5b9a<\/a>\u306a\u3069\u306e\u540c\u7b49\u306e\u30ce\u30f3\u30d1\u30e9\u30e1\u30c8\u30ea\u30c3\u30af\u691c\u5b9a\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4eee\u5b9a #2: \u5206\u6563\u304c\u7b49\u3057\u3044<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">ANOVA \u306f\u3001\u30b5\u30f3\u30d7\u30eb\u306e\u62bd\u51fa\u5143\u3068\u306a\u308b\u6bcd\u96c6\u56e3\u306e\u5206\u6563\u304c\u7b49\u3057\u3044\u3068\u4eee\u5b9a\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3> <strong><span style=\"color: #000000;\">R \u3067\u3053\u306e\u4eee\u8aac\u3092\u78ba\u8a8d\u3059\u308b\u65b9\u6cd5:<\/span><\/strong><\/h3>\n<p> <span style=\"color: #000000;\">R \u3067\u306f\u3001\u6b21\u306e 2 \u3064\u306e\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u4f7f\u7528\u3057\u3066\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u7bb1\u3072\u3052\u56f3\u3092\u4f7f\u7528\u3057\u3066\u4eee\u8aac\u3092\u8996\u899a\u7684\u306b\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u30d0\u30fc\u30c8\u30ec\u30c3\u30c8\u691c\u5b9a\u306a\u3069\u306e\u6b63\u5f0f\u306a\u7d71\u8a08\u691c\u5b9a\u3092\u4f7f\u7528\u3057\u3066\u4eee\u8aac\u3092\u691c\u5b9a\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u4ee5\u524d\u306b\u4f5c\u6210\u3057\u305f\u3082\u306e\u3068\u540c\u3058\u507d\u306e\u6e1b\u91cf\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066\u3001\u3053\u308c\u3092\u884c\u3046\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u7bb1\u3072\u3052\u56f3\u3092\u4f5c\u6210\u3057\u307e\u3059\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;\">\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u4f53\u91cd\u6e1b\u5c11\u306e\u5206\u6563\u306f\u3001\u5404\u7bb1\u3072\u3052\u56f3\u306e\u9577\u3055\u306b\u3088\u3063\u3066\u89b3\u5bdf\u3067\u304d\u307e\u3059\u3002\u30dc\u30c3\u30af\u30b9\u304c\u9577\u3044\u307b\u3069\u3001\u5206\u6563\u306f\u5927\u304d\u304f\u306a\u308a\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u30d7\u30ed\u30b0\u30e9\u30e0 A \u304a\u3088\u3073\u30d7\u30ed\u30b0\u30e9\u30e0 B \u3068\u6bd4\u8f03\u3057\u3066\u3001\u30d7\u30ed\u30b0\u30e9\u30e0 C \u306e\u53c2\u52a0\u8005\u306e\u5206\u6563\u304c\u308f\u305a\u304b\u306b\u9ad8\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \u30d0\u30fc\u30c8\u30ec\u30c3\u30c8 \u30c6\u30b9\u30c8\u3092\u5b9f\u884c\u3057\u307e\u3059\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\/ja\/r\u3066\u3099\u306e\u30cf\u3099\u30fc\u30c8\u30ec\u30c3\u30c8\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener\">\u30d0\u30fc\u30c8\u30ec\u30c3\u30c8\u691c\u5b9a\u3067<\/a>\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u306e\u5206\u6563\u304c\u7b49\u3057\u3044\u3068\u3044\u3046\u5e30\u7121\u4eee\u8aac\u3068\u3001\u30b5\u30f3\u30d7\u30eb\u306e\u5206\u6563\u304c\u7b49\u3057\u3044\u3068\u3044\u3046\u5bfe\u7acb\u4eee\u8aac\u3092\u691c\u5b9a\u3057\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001\u691c\u5b9a\u306e p \u5024\u306f<strong>0.01599<\/strong>\u3067\u3001\u30a2\u30eb\u30d5\u30a1 \u30ec\u30d9\u30eb\u306e 0.05 \u3088\u308a\u3082\u4f4e\u304f\u306a\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u30b5\u30f3\u30d7\u30eb\u306e\u5206\u6563\u304c\u3059\u3079\u3066\u540c\u3058\u3067\u306f\u306a\u3044\u3053\u3068\u3092\u793a\u5506\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u3053\u306e\u524d\u63d0\u304c\u5c0a\u91cd\u3055\u308c\u306a\u3044\u5834\u5408\u306f\u3069\u3046\u3059\u308c\u3070\u3088\u3044\u3067\u3059\u304b:<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u306b\u3001<\/span><span style=\"color: #000000;\">\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001\u5404\u30b0\u30eb\u30fc\u30d7\u304c\u540c\u3058\u30b5\u30f3\u30d7\u30eb \u30b5\u30a4\u30ba\u3067\u3042\u308b\u9650\u308a\u3001\u7b49\u5206\u6563\u306e\u4eee\u5b9a\u306e\u9055\u53cd\u306b\u5bfe\u3057\u3066\u304b\u306a\u308a\u5805\u7262\u3067\u3042\u308b\u3068\u8003\u3048\u3089\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u305f\u3060\u3057\u3001\u30b5\u30f3\u30d7\u30eb \u30b5\u30a4\u30ba\u304c\u540c\u3058\u3067\u306f\u306a\u304f\u3001\u3053\u306e\u4eee\u5b9a\u306b\u5927\u304d\u304f\u9055\u53cd\u3059\u308b\u5834\u5408\u306f\u3001\u4ee3\u308f\u308a\u306b\u3001\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306e\u30ce\u30f3\u30d1\u30e9\u30e1\u30c8\u30ea\u30c3\u30af \u30d0\u30fc\u30b8\u30e7\u30f3\u3067\u3042\u308b<a href=\"https:\/\/statorials.org\/ja\/\u30af\u30e9\u30b9\u30ab\u30eb\u30fb\u30a6\u30a9\u30ea\u30b9\u30fb\u30c6\u30b9\u30c8\/\" target=\"_blank\" rel=\"noopener\">\u30af\u30e9\u30b9\u30ab\u30eb \u30a6\u30a9\u30ea\u30b9\u691c\u5b9a<\/a>\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u524d\u63d0 #3: \u72ec\u7acb\u6027<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">ANOVA \u306f\u6b21\u306e\u3053\u3068\u3092\u524d\u63d0\u3068\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u89b3\u5bdf\u306f\u3001\u4ed6\u306e\u3059\u3079\u3066\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u89b3\u5bdf\u304b\u3089\u72ec\u7acb\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5404\u30b0\u30eb\u30fc\u30d7\u5185\u306e\u89b3\u5bdf\u7d50\u679c\u306f\u3001\u30e9\u30f3\u30c0\u30e0\u306a\u30b5\u30f3\u30d7\u30eb\u306b\u3088\u3063\u3066\u5f97\u3089\u308c\u307e\u3057\u305f\u3002<\/span><\/li>\n<\/ul>\n<h3><strong><span style=\"color: #000000;\">\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3059\u308b\u65b9\u6cd5:<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u89b3\u6e2c\u5024\u304c\u72ec\u7acb\u3057\u3066\u3044\u308b\u3053\u3068\u3001\u304a\u3088\u3073\u305d\u308c\u3089\u304c\u30e9\u30f3\u30c0\u30e0\u306a\u30b5\u30f3\u30d7\u30eb\u306b\u3088\u3063\u3066\u5f97\u3089\u308c\u305f\u3082\u306e\u3067\u3042\u308b\u3053\u3068\u3092\u691c\u8a3c\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3067\u304d\u308b\u6b63\u5f0f\u306a\u30c6\u30b9\u30c8\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/span><span style=\"color: #000000;\">\u3053\u306e\u4eee\u5b9a\u3092\u6e80\u305f\u3059\u552f\u4e00\u306e\u65b9\u6cd5\u306f\u3001\u30e9\u30f3\u30c0\u30e0\u5316\u3055\u308c\u305f\u8a2d\u8a08\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<h3><strong><span style=\"color: #000000;\">\u3053\u306e\u524d\u63d0\u304c\u5c0a\u91cd\u3055\u308c\u306a\u3044\u5834\u5408\u306f\u3069\u3046\u3059\u308c\u3070\u3088\u3044\u3067\u3059\u304b:<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u6b8b\u5ff5\u306a\u304c\u3089\u3001\u3053\u306e\u524d\u63d0\u304c\u6e80\u305f\u3055\u308c\u306a\u3044\u5834\u5408\u3001\u3067\u304d\u308b\u3053\u3068\u306f\u3042\u307e\u308a\u3042\u308a\u307e\u305b\u3093\u3002\u7c21\u5358\u306b\u8a00\u3048\u3070\u3001\u5404\u30b0\u30eb\u30fc\u30d7\u306e\u89b3\u6e2c\u5024\u304c\u4ed6\u306e\u30b0\u30eb\u30fc\u30d7\u306e\u89b3\u6e2c\u5024\u304b\u3089\u72ec\u7acb\u3057\u3066\u3044\u306a\u3044\u3088\u3046\u306a\u65b9\u6cd5\u3067\u30c7\u30fc\u30bf\u304c\u53ce\u96c6\u3055\u308c\u305f\u5834\u5408\u3001\u307e\u305f\u306f\u5404\u30b0\u30eb\u30fc\u30d7\u5185\u306e\u89b3\u6e2c\u5024\u304c\u30e9\u30f3\u30c0\u30e0\u5316\u30d7\u30ed\u30bb\u30b9\u306b\u3088\u3063\u3066\u53d6\u5f97\u3055\u308c\u306a\u304b\u3063\u305f\u5834\u5408\u3001ANOVA \u306e\u7d50\u679c\u306f\u4fe1\u983c\u3067\u304d\u306a\u304f\u306a\u308a\u307e\u3059\u3002 \u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4eee\u5b9a\u304c\u6e80\u305f\u3055\u308c\u306a\u3044\u5834\u5408\u3001\u6700\u5584\u306e\u65b9\u6cd5\u306f\u3001\u30e9\u30f3\u30c0\u30e0\u5316\u3055\u308c\u305f\u8a08\u753b\u3092\u4f7f\u7528\u3057\u3066\u5b9f\u9a13\u3092\u518d\u4f5c\u6210\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u53c2\u8003\u6587\u732e\uff1a<\/strong><\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">R \u3067\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">Excel \u3067\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e00\u5143\u914d\u7f6e\u5206\u6563\u5206\u6790\u306f\u3001 3 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