{"id":1312,"date":"2023-07-26T22:05:53","date_gmt":"2023-07-26T22:05:53","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%a6-%e1%84%83%e1%85%a1%e1%84%8c%e1%85%ae%e1%86%bc-%e1%84%89%e1%85%a5%e1%86%ab%e1%84%92%e1%85%a7%e1%86%bc-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1%e1%84%85%e1%85%b3%e1%86%af-%e1%84%91\/"},"modified":"2023-07-26T22:05:53","modified_gmt":"2023-07-26T22:05:53","slug":"r%e1%84%8b%e1%85%a6-%e1%84%83%e1%85%a1%e1%84%8c%e1%85%ae%e1%86%bc-%e1%84%89%e1%85%a5%e1%86%ab%e1%84%92%e1%85%a7%e1%86%bc-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1%e1%84%85%e1%85%b3%e1%86%af-%e1%84%91","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%a6-%e1%84%83%e1%85%a1%e1%84%8c%e1%85%ae%e1%86%bc-%e1%84%89%e1%85%a5%e1%86%ab%e1%84%92%e1%85%a7%e1%86%bc-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1%e1%84%85%e1%85%b3%e1%86%af-%e1%84%91\/","title":{"rendered":"R\uc5d0\uc11c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \uacb0\uacfc\ub97c \ud50c\ub86f\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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R\uc5d0\uc11c \ub2e8\uc21c \uc120\ud615 \ud68c\uadc0\ub97c<\/a> \uc218\ud589\ud560 \ub54c \ub2e8\uc77c \uc608\uce21 \ubcc0\uc218\uc640 \ub2e8\uc77c \uc751\ub2f5 \ubcc0\uc218<\/a> \ub85c\ub9cc \uc791\uc5c5\ud558\uae30 \ub54c\ubb38\uc5d0 \uc801\ud569 \ud68c\uadc0\uc120\uc744 \uc2dc\uac01\ud654\ud558\ub294 \uac83\uc774 \uc27d\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\uc608\ub97c \ub4e4\uc5b4, \ub2e4\uc74c \ucf54\ub4dc\ub294 \ub2e8\uc21c \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378\uc744 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub9de\ucd94\uace0 \uacb0\uacfc\ub97c \uadf8\ub9ac\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n

 #create dataset\n<\/span>data <- 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#fit simple linear regression model\n<\/span>model <- lm(y ~ x, data = data)\n\n#create scatterplot of data\n<\/span>plot(data$x, data$y)\n\n#add fitted regression line\n<\/span>abline(model)\n<\/strong><\/pre>\n
\"\uc0b0\uc810\ub3c4\ub97c<\/p>\n
 \ub300\uc2e0, \ubaa8\ub378\uc5d0\uc11c \ub2e4\ub978 \uc608\uce21 \ubcc0\uc218\uc758 \uc874\uc7ac\ub97c \uc81c\uc5b4\ud558\uba74\uc11c<\/em> \ubc18\uc751 \ubcc0\uc218\uc640 \uc608\uce21 \ubcc0\uc218 \uc0ac\uc774\uc758 \uad00\uacc4\ub97c \ud45c\uc2dc\ud558\ub294 \uac1c\ubcc4 \ub3c4\ud45c\uc778 \ucd94\uac00 \ubcc0\uc218 \ub3c4\ud45c<\/strong> (“\ubd80\ubd84 \ud68c\uadc0 \ub3c4\ud45c”\ub77c\uace0\ub3c4 \ud568)\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\uace0 \ucd94\uac00\ub41c \ubcc0\uc218 \ud50c\ub86f\uc744 \uc0ac\uc6a9\ud558\uc5ec \uacb0\uacfc\ub97c \uc2dc\uac01\ud654\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: R\uc5d0 \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \uacb0\uacfc \ub3c4\ud45c\ud654<\/strong><\/span><\/h3>\n
 \ub0b4\uc7a5\ub41c mtcars<\/strong> \ub370\uc774\ud130 \uc138\ud2b8\ub97c \uc0ac\uc6a9\ud558\uc5ec R\uc758 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub2e4\uc74c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\uc6a9\ud55c\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 #fit multiple linear regression model\nmodel <- lm(mpg ~ disp + hp + drat, data = mtcars)\n<\/span>\n#view results of model\nsummary(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(>|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
 \uacb0\uacfc\uc5d0\uc11c \uac01 \uacc4\uc218\uc758 p-\uac12\uc774 0.1\ubcf4\ub2e4 \uc791\uc740 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e8\uc21c\ud654\ub97c \uc704\ud574 \uac01 \uc608\uce21 \ubcc0\uc218\uac00 \uc911\uc694\ud558\uba70 \ubaa8\ub378\uc5d0 \ud3ec\ud568\ub418\uc5b4\uc57c \ud55c\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00\ub41c \ubcc0\uc218\uc758 \ud50c\ub86f\uc744 \uc0dd\uc131\ud558\ub824\uba74 car<\/strong> \ud328\ud0a4\uc9c0\uc758 avPlots()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 #load car package\nlibrary(car)\n<\/span>\n#produce added variable plots\navPlots(model)<\/span>\n<\/span><\/strong><\/pre>\n
\"R\uc5d0<\/p>\n
 \uac01 \ud50c\ub86f\uc744 \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uadf8\ub7ec\ub098 \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0\ub97c<\/a> \uc218\ud589\ud560 \uacbd\uc6b0 \uc608\uce21 \ubcc0\uc218\uac00 \uc5ec\ub7ec \uac1c \uc788\uace0 \ub2e8\uc21c\ud788 2\ucc28\uc6d0 \uadf8\ub798\ud504\uc5d0 \ud68c\uadc0\uc120\uc744 \uadf8\ub9b4 \uc218 \uc5c6\uae30 \ub54c\ubb38\uc5d0 \uacb0\uacfc\ub97c \uc2dc\uac01\ud654\ud558\uae30\uac00 \uc5b4\ub835\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n