{"id":2491,"date":"2023-07-22T01:04:49","date_gmt":"2023-07-22T01:04:49","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8a%e1%85%a1%e1%86%bc%e1%84%87%e1%85%a7%e1%86%af-%e1%84%87%e1%85%b5%e1%84%80%e1%85%ad\/"},"modified":"2023-07-22T01:04:49","modified_gmt":"2023-07-22T01:04:49","slug":"r%e1%84%8b%e1%85%b4-%e1%84%8a%e1%85%a1%e1%86%bc%e1%84%87%e1%85%a7%e1%86%af-%e1%84%87%e1%85%b5%e1%84%80%e1%85%ad","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%8a%e1%85%a1%e1%86%bc%e1%84%87%e1%85%a7%e1%86%af-%e1%84%87%e1%85%b5%e1%84%80%e1%85%ad\/","title":{"rendered":"R\uc5d0\uc11c \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ko\/\u1103\u1161\u11ab\u1107\u1161\u11bc\u1112\u1163\u11bc-\u110b\u1161\u1102\u1169\u1107\u1161\/\" target=\"_blank\" rel=\"noopener\">\uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc740<\/a> 3\uac1c \uc774\uc0c1\uc758 \ub3c5\ub9bd \uadf8\ub8f9 \ud3c9\uade0 \uac04\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ud55c \ucc28\uc774\uac00 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc5d0\uc11c\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uadc0\ubb34 \uac00\uc124\uacfc \ub300\ub9bd \uac00\uc124\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>H <sub>0<\/sub><\/strong> : \ubaa8\ub4e0 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub3d9\uc77c\ud569\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>H <sub>A<\/sub><\/strong> : \ubaa8\ub4e0 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub3d9\uc77c\ud55c \uac83\uc740 \uc544\ub2d9\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">ANOVA\uc758 \uc804\uccb4 <a href=\"https:\/\/statorials.org\/ko\/anova-f-\u1100\u1161\u11b9-p-\u1100\u1161\u11b9\/\" target=\"_blank\" rel=\"noopener\">p-\uac12\uc774<\/a> \ud2b9\uc815 \uc720\uc758 \uc218\uc900(\uc608: \u03b1 = 0.05)\ubcf4\ub2e4 \ub0ae\uc73c\uba74 \uadc0\ubb34 \uac00\uc124\uc744 \uae30\uac01\ud558\uace0 \ubaa8\ub4e0 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub3d9\uc77c\ud558\uc9c0 \uc54a\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9bd\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc5b4\ub5a4 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub2e4\ub978\uc9c0 \ud655\uc778\ud558\uae30 \uc704\ud574 <strong>\uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c<\/strong> \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ub2e4\uc74c\uacfc \uac19\uc740 \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\ud22c\ud0a4 \ubc29\uc2dd<\/span><\/li>\n<li> <span style=\"color: #000000;\">Scheffe \ubc29\ubc95<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ubcf8\ud398\ub85c\ub2c8 \ubc29\ubc95<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud640\ub984 \ubc29\ubc95<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>\uc608: R\uc758 \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uad50\uc0ac\uac00 \uc138 \uac00\uc9c0 \ub2e4\ub978 \ud559\uc2b5 \ubc29\ubc95\uc774 \ud559\uc0dd\ub4e4 \uc0ac\uc774\uc5d0 \ub2e4\ub978 \uc2dc\ud5d8 \uc810\uc218\ub85c \uc774\uc5b4\uc9c0\ub294\uc9c0 \uc5ec\ubd80\ub97c \uc54c\uace0 \uc2f6\uc5b4\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud14c\uc2a4\ud2b8\ud558\uae30 \uc704\ud574 \uadf8\ub140\ub294 \uac01 \ud559\uc2b5 \uae30\uc220\uc744 \uc0ac\uc6a9\ud558\ub3c4\ub85d 10\uba85\uc758 \ud559\uc0dd\uc744 <a href=\"https:\/\/statorials.org\/ko\/\u1106\u116e\u110c\u1161\u11a8\u110b\u1171-\u1109\u1165\u11ab\u1110\u1162\u11a8\u1100\u116a-\u1106\u116e\u110c\u1161\u11a8\u110b\u1171-\u1112\u1161\u11af\u1103\u1161\u11bc\/\" target=\"_blank\" rel=\"noopener\">\ubb34\uc791\uc704\ub85c \ud560\ub2f9<\/a> \ud558\uace0 \uadf8\ub4e4\uc758 \uc2dc\ud5d8 \uacb0\uacfc\ub97c \uae30\ub85d\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">R\uc5d0\uc11c \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc744 \uc218\ud589\ud558\uc5ec \uc138 \uadf8\ub8f9 \uac04\uc758 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218 \ucc28\uc774\ub97c \ud14c\uc2a4\ud2b8\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create data frame<\/span>\ndf &lt;- data.frame(technique = rep(c(\" <span style=\"color: #ff0000;\">tech1<\/span> \", \" <span style=\"color: #ff0000;\">tech2<\/span> \", \" <span style=\"color: #ff0000;\">tech3<\/span> \"), each= <span style=\"color: #008000;\">10<\/span> ),\n                 score = c(76, 77, 77, 81, 82, 82, 83, 84, 85, 89,\n                           81, 82, 83, 83, 83, 84, 87, 90, 92, 93,\n                           77, 78, 79, 88, 89, 90, 91, 95, 95, 98))\n\n<span style=\"color: #008080;\">#perform one-way ANOVA\n<\/span>model &lt;- aov(score ~ technique, data = df)\n\n<span style=\"color: #008080;\">#view output of ANOVA\n<\/span>summary(model)\n\n            Df Sum Sq Mean Sq F value Pr(&gt;F)  \ntechnical 2 211.5 105.73 3.415 0.0476 *\nResiduals 27 836.0 30.96                 \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">ANOVA\uc758 \uc804\uccb4 p-\uac12(0.0476)\uc740 \u03b1 = 0.05\ubcf4\ub2e4 \uc791\uc73c\ubbc0\ub85c \uac01 \ud559\uc2b5 \uae30\ubc95\uc5d0 \ub300\ud574 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218\uac00 \ub3d9\uc77c\ud558\ub2e4\ub294 \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc5b4\ub5a4 \uadf8\ub8f9\uc774 \ub2e4\ub978 \ud3c9\uade0\uc744 \uac00\uc9c0\uace0 \uc788\ub294\uc9c0 \ud655\uc778\ud558\uae30 \uc704\ud574 \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ud22c\ud0a4 \ubc29\uc2dd<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uac01 \uadf8\ub8f9\uc758 \ud45c\ubcf8 \ud06c\uae30\uac00 \ub3d9\uc77c\ud55c \uacbd\uc6b0 Tukey\uc758 \uc0ac\ud6c4 \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\ub294 \uac83\uc774 \uac00\uc7a5 \uc88b\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub0b4\uc7a5\ub41c <strong>TukeyHSD()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc5d0\uc11c Tukey \uc0ac\ud6c4 \uba54\uc18c\ub4dc\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#perform the Tukey post-hoc method<\/span>\nTukeyHSD(model, conf. <span style=\"color: #3366ff;\">level<\/span> = <span style=\"color: #008000;\">.95<\/span> )\n\n  Tukey multiple comparisons of means\n    95% family-wise confidence level\n\nFit: aov(formula = score ~ technique, data = df)\n\n$technical\n            diff lwr upr p adj\ntech2-tech1 4.2 -1.9700112 10.370011 0.2281369\ntech3-tech1 6.4 0.2299888 12.570011 0.0409017\ntech3-tech2 2.2 -3.9700112 8.370011 0.6547756<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c 0.05 \ubbf8\ub9cc\uc778 \uc720\uc77c\ud55c p-\uac12(\u201c <strong>p adj<\/strong> \u201d)\uc740 \uae30\ubc95\uacfc \uae30\ubc95 3\uc758 \ucc28\uc774\uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub530\ub77c\uc11c \uae30\ubc95 1\uacfc \uae30\ubc95 3\uc744 \uc0ac\uc6a9\ud55c \ud559\uc0dd\ub4e4 \uc0ac\uc774\uc758 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218\uc5d0\ub294 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\ub9cc \uc788\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Scheffe \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Scheffe \ubc29\ubc95\uc740 \uac00\uc7a5 \ubcf4\uc218\uc801\uc778 \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50 \ubc29\ubc95\uc774\uba70 \uadf8\ub8f9 \ud3c9\uade0\uc744 \ube44\uad50\ud560 \ub54c \uac00\uc7a5 \ub113\uc740 \uc2e0\ub8b0 \uad6c\uac04\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><a href=\"https:\/\/cran.r-project.org\/web\/packages\/DescTools\/DescTools.pdf\" target=\"_blank\" rel=\"noopener\">DescTools<\/a> \ud328\ud0a4\uc9c0\uc758 <strong>ScheffeTest()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc5d0\uc11c Scheffe \uc0ac\ud6c4 \uba54\uc11c\ub4dc\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">library<\/span> (DescTools)<\/span>\n\n#perform the Scheffe post-hoc method<\/span>\nScheffeTest(model)\n\n  Posthoc multiple comparisons of means: Scheffe Test \n    95% family-wise confidence level\n\n$technical\n            diff lwr.ci upr.ci pval    \ntech2-tech1 4.2 -2.24527202 10.645272 0.2582    \ntech3-tech1 6.4 -0.04527202 12.845272 0.0519 .  \ntech3-tech2 2.2 -4.24527202 8.645272 0.6803    \n\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1'''156<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c \uc6b0\ub9ac\ub294 0.05\ubcf4\ub2e4 \ub0ae\uc740 p-\uac12\uc774 \uc5c6\uc74c\uc744 \uc54c \uc218 \uc788\uc73c\ubbc0\ub85c \uadf8\ub8f9 \uac04 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218\uc5d0\ub294 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\uac00 \uc5c6\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ubcf8\ud398\ub85c\ub2c8 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uacc4\ud68d\ub41c \uc30d\ubcc4 \ube44\uad50 \uc138\ud2b8\ub97c \uc218\ud589\ud558\ub824\ub294 \uacbd\uc6b0 Bonferroni \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\ub294 \uac83\uc774 \uac00\uc7a5 \uc88b\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">R\uc5d0\uc11c \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Bonferroni \uc0ac\ud6c4 \ubc29\ubc95\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#perform the Bonferroni post-hoc method\n<span style=\"color: #000000;\">pairwise. <span style=\"color: #3366ff;\">t<\/span> . <span style=\"color: #3366ff;\">test<\/span> (df$score, df$technique, p. <span style=\"color: #3366ff;\">adj<\/span> = ' <span style=\"color: #ff0000;\">bonferroni<\/span> ')<\/span>\n<\/span>\n\tPairwise comparisons using t tests with pooled SD \n\ndata: df$score and df$technique \n\n      tech1 tech2\ntech2 0.309 -    \ntech3 0.048 1.000\n\nP value adjustment method: bonferroni<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c 0.05\ubcf4\ub2e4 \uc791\uc740 \uc720\uc77c\ud55c p-\uac12\uc740 \uae30\ubc95\uacfc \uae30\ubc95 3\uc758 \ucc28\uc774\uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub530\ub77c\uc11c \uae30\ubc95 1\uacfc \uae30\ubc95 3\uc744 \uc0ac\uc6a9\ud55c \ud559\uc0dd\ub4e4 \uc0ac\uc774\uc758 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218\uc5d0\ub294 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\ub9cc \uc788\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ud640\ub984 \ubc29\ubc95<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Holm \ubc29\ubc95\uc740 \uacc4\ud68d\ub41c \uc77c\ub828\uc758 \uc30d\ubcc4 \ube44\uad50\ub97c \ubbf8\ub9ac \uc218\ud589\ud558\ub824\ub294 \uacbd\uc6b0\uc5d0\ub3c4 \uc0ac\uc6a9\ub418\uba70 Bonferroni \ubc29\ubc95\ubcf4\ub2e4 \uac80\uc815\ub825\uc774 \ud6e8\uc52c \ub354 \ub192\uc740 \uacbd\ud5a5\uc774 \uc788\uc73c\ubbc0\ub85c \uc120\ud638\ub418\ub294 \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">R\uc5d0\uc11c \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Holm \uc0ac\ud6c4 \uba54\uc11c\ub4dc\ub97c \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#perform the Holm post-hoc method\n<span style=\"color: #000000;\">pairwise. <span style=\"color: #3366ff;\">t<\/span> . <span style=\"color: #3366ff;\">test<\/span> (df$score, df$technique, p. <span style=\"color: #3366ff;\">adj<\/span> = ' <span style=\"color: #ff0000;\">holm<\/span> ')<\/span>\n<\/span>\n\tPairwise comparisons using t tests with pooled SD \n\ndata: df$score and df$technique \n\n      tech1 tech2\ntech2 0.206 -    \ntech3 0.048 0.384\n\nP value adjustment method: holm<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\uc5d0\uc11c 0.05\ubcf4\ub2e4 \uc791\uc740 \uc720\uc77c\ud55c p-\uac12\uc740 \uae30\ubc95\uacfc \uae30\ubc95 3\uc758 \ucc28\uc774\uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub530\ub77c\uc11c \ub2e4\uc2dc \uae30\uc220 1\uacfc \uae30\uc220 3\uc744 \uc0ac\uc6a9\ud55c \ud559\uc0dd\ub4e4 \uc0ac\uc774\uc758 \ud3c9\uade0 \uc2dc\ud5d8 \uc810\uc218\uc5d0\ub294 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ubbf8\ud55c \ucc28\uc774\ub9cc \uc788\ub2e4\ub294 \uacb0\ub860\uc744 \ub0b4\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc790\uc2b5\uc11c\uc5d0\uc11c\ub294 \ubd84\uc0b0 \ubd84\uc11d \ubc0f \uc0ac\ud6c4 \ud14c\uc2a4\ud2b8\uc5d0 \ub300\ud55c \ucd94\uac00 \uc815\ubcf4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/anova-f-\u1100\u1161\u11b9-p-\u1100\u1161\u11b9\/\" target=\"_blank\" rel=\"noopener\">ANOVA\uc5d0\uc11c F\uac12\uacfc P\uac12\uc744 \ud574\uc11d\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/anova-\u1100\u1167\u11af\u1100\u116a\u1105\u1173\u11af-\u1107\u1169\u1100\u1169\u1112\u1161\u1102\u1173\u11ab-\u1107\u1161\u11bc\u1107\u1165\u11b8\/\" target=\"_blank\" rel=\"noopener\">\uc804\uccb4 \uac00\uc774\ub4dc: ANOVA \uacb0\uacfc \ubcf4\uace0 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1110\u116e\u110f\u1175-vs-\u1107\u1169\u11ab\u1111\u1166\u1105\u1169\u1102\u1175-vs-\u1109\u1170\u1111\u1166\/\" target=\"_blank\" rel=\"noopener\">\ud130\ud0a4 \ub300. \ubcf8\ud398\ub85c\ub2c8 vs. Scheffe: \uc5b4\ub5a4 \ud14c\uc2a4\ud2b8\ub97c \uc0ac\uc6a9\ud574\uc57c \ud569\ub2c8\uae4c?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc740 3\uac1c \uc774\uc0c1\uc758 \ub3c5\ub9bd \uadf8\ub8f9 \ud3c9\uade0 \uac04\uc5d0 \ud1b5\uacc4\uc801\uc73c\ub85c \uc720\uc758\ud55c \ucc28\uc774\uac00 \uc788\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc77c\uc6d0 \ubd84\uc0b0 \ubd84\uc11d\uc5d0\uc11c\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uadc0\ubb34 \uac00\uc124\uacfc \ub300\ub9bd \uac00\uc124\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4. H 0 : \ubaa8\ub4e0 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub3d9\uc77c\ud569\ub2c8\ub2e4. H A : \ubaa8\ub4e0 \uadf8\ub8f9 \ud3c9\uade0\uc774 \ub3d9\uc77c\ud55c \uac83\uc740 \uc544\ub2d9\ub2c8\ub2e4. ANOVA\uc758 \uc804\uccb4 p-\uac12\uc774 \ud2b9\uc815 \uc720\uc758 \uc218\uc900(\uc608: \u03b1 = 0.05)\ubcf4\ub2e4 \ub0ae\uc73c\uba74 \uadc0\ubb34 \uac00\uc124\uc744 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-2491","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R - Statorials\uc5d0\uc11c \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uc804\uccb4 \uc608\uc81c\ub97c \ud3ec\ud568\ud558\uc5ec R\uc5d0\uc11c \uc0ac\ud6c4 \uc30d\ubcc4 \ube44\uad50\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ko\/r\u110b\u1174-\u110a\u1161\u11bc\u1107\u1167\u11af-\u1107\u1175\u1100\u116d\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R - 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