{"id":1640,"date":"2023-07-25T13:26:30","date_gmt":"2023-07-25T13:26:30","guid":{"rendered":"https:\/\/statorials.org\/ko\/r-%e1%84%80%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%8c%e1%85%a5%e1%86%bc\/"},"modified":"2023-07-25T13:26:30","modified_gmt":"2023-07-25T13:26:30","slug":"r-%e1%84%80%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%8c%e1%85%a5%e1%86%bc","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r-%e1%84%80%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%8c%e1%85%a5%e1%86%bc\/","title":{"rendered":"R\uc758 \uace1\uc120 \ud53c\ud305(\uc608\uc81c \ud3ec\ud568)"},"content":{"rendered":"

<\/p>\n

\n

\uc885\uc885 R \uace1\uc120\uc5d0 \uac00\uc7a5 \uc798 \ub9de\ub294 \ubc29\uc815\uc2dd\uc744 \ucc3e\uace0 \uc2f6\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n

\"R\uc758<\/p>\n

\ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc81c \uc5d0\uc11c\ub294 \ud3f4\ub9ac()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc758 \ub370\uc774\ud130\uc5d0 \uace1\uc120\uc744 \ub9de\ucd94\ub294 \ubc29\ubc95\uacfc \ub370\uc774\ud130\uc5d0 \uac00\uc7a5 \uc801\ud569\ud55c \uace1\uc120\uc744 \uacb0\uc815\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n

1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131 \ubc0f \uc2dc\uac01\ud654<\/strong><\/span><\/h3>\n

\uba3c\uc800 \uac00\uc9dc \ub370\uc774\ud130 \uc138\ud2b8\ub97c \ub9cc\ub4e0 \ub2e4\uc74c \uc0b0\uc810\ub3c4\ub97c \ub9cc\ub4e4\uc5b4 \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n

 #create data frame\n<\/span>df <- data. frame<\/span> (x=1:15,\n                 y=c(3, 14, 23, 25, 23, 15, 9, 5, 9, 13, 17, 24, 32, 36, 46))\n\n#create a scatterplot of x vs. y\n<\/span>plot(df$x, df$y, pch= 19<\/span> , xlab=' x<\/span> ', ylab=' y<\/span> ')<\/strong> <\/pre>\n
\"\"<\/p>\n
 2\ub2e8\uacc4: \uc5ec\ub7ec \uace1\uc120 \uc870\uc815<\/strong><\/span><\/h3>\n
 \uadf8\ub7f0 \ub2e4\uc74c \uc5ec\ub7ec \ub2e4\ud56d\uc2dd \ud68c\uadc0 \ubaa8\ub378\uc744 \ub370\uc774\ud130\uc5d0 \ub9de\ucd94\uace0 \ub3d9\uc77c\ud55c \ud50c\ub86f\uc5d0\uc11c \uac01 \ubaa8\ub378\uc758 \uace1\uc120\uc744 \uc2dc\uac01\ud654\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 #fit polynomial regression models up to degree 5\n<\/span>fit1 <- lm(y~x, data=df)\nfit2 <- lm(y~poly(x,2,raw= TRUE<\/span> ), data=df)\nfit3 <- lm(y~poly(x,3,raw= TRUE<\/span> ), data=df)\nfit4 <- lm(y~poly(x,4,raw= TRUE<\/span> ), data=df)\nfit5 <- lm(y~poly(x,5,raw= TRUE<\/span> ), data=df)<\/span>\n\n#create a scatterplot of x vs. y\n<\/span>plot(df$x, df$y, pch=19, xlab=' x<\/span> ', ylab=' y<\/span> ')\n\n#define x-axis values\n<\/span>x_axis <- seq(1, 15, length= 15<\/span> )\n\n#add curve of each model to plot\n<\/span>lines(x_axis, predict(fit1, data. frame<\/span> (x=x_axis)), col=' green<\/span> ')\nlines(x_axis, predict(fit2, data. frame<\/span> (x=x_axis)), col=' red<\/span> ')\nlines(x_axis, predict(fit3, data. frame<\/span> (x=x_axis)), col=' purple<\/span> ')\nlines(x_axis, predict(fit4, data. frame<\/span> (x=x_axis)), col=' blue<\/span> ')\nlines(x_axis, predict(fit5, data. frame<\/span> (x=x_axis)), col=' orange<\/span> ')\n<\/strong><\/pre>\n
\"\"<\/p>\n
 \uc5b4\ub5a4 \uace1\uc120\uc774 \ub370\uc774\ud130\uc5d0 \uac00\uc7a5 \uc798 \ub9de\ub294\uc9c0 \uacb0\uc815\ud558\ub824\uba74 \uac01 \ubaa8\ub378\uc758 \uc870\uc815\ub41c R \uc81c\uacf1\uc744<\/a> \ubcf4\uba74 \ub429\ub2c8\ub2e4.<\/span><\/p>\n
 \uc774 \uac12\uc740 \uc608\uce21 \ubcc0\uc218\uc758 \uc218\uc5d0 \ub9de\uac8c \uc870\uc815\ub41c \ubaa8\ub378\uc758 \uc608\uce21 \ubcc0\uc218\ub85c \uc124\uba85\ud560 \uc218 \uc788\ub294 \ubc18\uc751 \ubcc0\uc218\uc758 \ubcc0\ub3d9 \ube44\uc728\uc744 \uc54c\ub824\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #calculated adjusted R-squared of each model\n<\/span>summary(fit1)$adj. r<\/span> . squared<\/span>\nsummary(fit2)$adj. r<\/span> . squared<\/span>\nsummary(fit3)$adj. r<\/span> . squared<\/span>\nsummary(fit4)$adj. r<\/span> . squared<\/span>\nsummary(fit5)$adj. r<\/span> . squared<\/span>\n\n[1] 0.3144819\n[1] 0.5186706\n[1] 0.7842864\n[1] 0.9590276\n[1] 0.9549709\n<\/strong><\/pre>\n
 \uacb0\uacfc\uc5d0\uc11c \uc870\uc815\ub41c R-\uc81c\uacf1\uc774 \uac00\uc7a5 \ub192\uc740 \ubaa8\ub378\uc740 \uc870\uc815\ub41c R-\uc81c\uacf1\uc774 0.959<\/strong> \uc778 4\ucc28 \ub2e4\ud56d\uc2dd\uc784\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 3\ub2e8\uacc4: \ucd5c\uc885 \uace1\uc120 \uc2dc\uac01\ud654<\/strong><\/span><\/h3>\n
 \ub9c8\uc9c0\ub9c9\uc73c\ub85c 4\ucc28 \ub2e4\ud56d\uc2dd \ubaa8\ub378\uc758 \uace1\uc120\uc744 \uc0ac\uc6a9\ud558\uc5ec \uc0b0\uc810\ub3c4\ub97c \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 #create a scatterplot of x vs. y\n<\/span>plot(df$x, df$y, pch=19, xlab=' x<\/span> ', ylab=' y<\/span> ')\n\n#define x-axis values\n<\/span>x_axis <- seq(1, 15, length= 15<\/span> )\n\n#add curve of fourth-degree polynomial model\n<\/span>lines(x_axis, predict(fit4, data. frame<\/span> (x=x_axis)), col=' blue<\/span> ')\n<\/strong><\/pre>\n
\"R\uc758<\/p>\n
 summary()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 \uc904\uc5d0 \ub300\ud55c \ubc29\uc815\uc2dd\uc744 \uc5bb\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 summary(fit4)\n\nCall:\nlm(formula = y ~ poly(x, 4, raw = TRUE), data = df)\n\nResiduals:\n    Min 1Q Median 3Q Max \n-3.4490 -1.1732 0.6023 1.4899 3.0351 \n\nCoefficients:\n                         Estimate Std. Error t value Pr(>|t|)    \n(Intercept) -26.51615 4.94555 -5.362 0.000318 ***\npoly(x, 4, raw = TRUE)1 35.82311 3.98204 8.996 4.15e-06 ***\npoly(x, 4, raw = TRUE)2 -8.36486 0.96791 -8.642 5.95e-06 ***\npoly(x, 4, raw = TRUE)3 0.70812 0.08954 7.908 1.30e-05 ***\npoly(x, 4, raw = TRUE)4 -0.01924 0.00278 -6.922 4.08e-05 ***\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 2.424 on 10 degrees of freedom\nMultiple R-squared: 0.9707, Adjusted R-squared: 0.959 \nF-statistic: 82.92 on 4 and 10 DF, p-value: 1.257e-07\n<\/strong><\/pre>\n
 \uace1\uc120\uc758 \ubc29\uc815\uc2dd\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 y = -0.0192x 4<\/sup> + 0.7081x 3<\/sup> \u2013 8.3649x 2<\/sup> + 35.823x \u2013 26.516<\/span><\/p>\n
 \uc774 \ubc29\uc815\uc2dd\uc744 \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc608\uce21 \ubcc0\uc218\ub97c \uae30\ubc18\uc73c\ub85c \uc751\ub2f5 \ubcc0\uc218<\/a> \uc758 \uac12\uc744 \uc608\uce21\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4 x<\/em> = 4\uc774\uba74 y<\/em> = 23.34<\/strong> \ub77c\uace0 \uc608\uce21\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 y = -0.0192(4) 4<\/sup> + 0.7081(4) 3<\/sup> \u2013 8.3649(4) 2<\/sup> + 35.823(4) \u2013 26.516 = 23.34<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\ud56d\uc2dd \ud68c\uadc0 \uc18c\uac1c
<\/a> R\uc758 \ub2e4\ud56d\uc2dd \ud68c\uadc0(\ub2e8\uacc4\ubcc4)<\/a>
 R\uc5d0\uc11c seq \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\uc885\uc885 R \uace1\uc120\uc5d0 \uac00\uc7a5 \uc798 \ub9de\ub294 \ubc29\uc815\uc2dd\uc744 \ucc3e\uace0 \uc2f6\uc744 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc81c \uc5d0\uc11c\ub294 \ud3f4\ub9ac() \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc758 \ub370\uc774\ud130\uc5d0 \uace1\uc120\uc744 \ub9de\ucd94\ub294 \ubc29\ubc95\uacfc \ub370\uc774\ud130\uc5d0 \uac00\uc7a5 \uc801\ud569\ud55c \uace1\uc120\uc744 \uacb0\uc815\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4. 1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131 \ubc0f \uc2dc\uac01\ud654 \uba3c\uc800 \uac00\uc9dc \ub370\uc774\ud130 \uc138\ud2b8\ub97c \ub9cc\ub4e0 \ub2e4\uc74c \uc0b0\uc810\ub3c4\ub97c \ub9cc\ub4e4\uc5b4 \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. #create data frame df <- data. frame (x=1:15, y=c(3, […]<\/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-1640","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nR\uc758 \uace1\uc120 \ud53c\ud305(\uc608\uc81c \ud3ec\ud568) - Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 R\uc5d0\uc11c \uc810 \uad6c\ub984\uc5d0 \uace1\uc120\uc744 \ub9de\ucd94\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-\u1100\u1169\u11a8\u1109\u1165\u11ab-\u110c\u1169\u110c\u1165\u11bc\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R\uc758 \uace1\uc120 \ud53c\ud305(\uc608\uc81c \ud3ec\ud568) - Statorials\" \/>\n<meta property=\"og:description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 R\uc5d0\uc11c \uc810 \uad6c\ub984\uc5d0 \uace1\uc120\uc744 \ub9de\ucd94\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ko\/r-\u1100\u1169\u11a8\u1109\u1165\u11ab-\u110c\u1169\u110c\u1165\u11bc\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-25T13:26:30+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/courberaccordr1.png\" \/>\n<meta name=\"author\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\ubca4\uc790\ubbfc \uc564\ub354\uc2a8\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ko\/r-%e1%84%80%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%8c%e1%85%a5%e1%86%bc\/\",\"url\":\"https:\/\/statorials.org\/ko\/r-%e1%84%80%e1%85%a9%e1%86%a8%e1%84%89%e1%85%a5%e1%86%ab-%e1%84%8c%e1%85%a9%e1%84%8c%e1%85%a5%e1%86%bc\/\",\"name\":\"R\uc758 \uace1\uc120 \ud53c\ud305(\uc608\uc81c \ud3ec\ud568) - 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