{"id":2945,"date":"2023-07-19T23:13:05","date_gmt":"2023-07-19T23:13:05","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-lm%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a8%e1%84%89%e1%85%ae%e1%84%85%e1%85%b3%e1%86%af-%e1%84%8e%e1%85%ae%e1%84%8e%e1%85%ae%e1%86%af%e1%84%92%e1%85%a1%e1%86%b8\/"},"modified":"2023-07-19T23:13:05","modified_gmt":"2023-07-19T23:13:05","slug":"r%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-lm%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a8%e1%84%89%e1%85%ae%e1%84%85%e1%85%b3%e1%86%af-%e1%84%8e%e1%85%ae%e1%84%8e%e1%85%ae%e1%86%af%e1%84%92%e1%85%a1%e1%86%b8","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-lm%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a8%e1%84%89%e1%85%ae%e1%84%85%e1%85%b3%e1%86%af-%e1%84%8e%e1%85%ae%e1%84%8e%e1%85%ae%e1%86%af%e1%84%92%e1%85%a1%e1%86%b8\/","title":{"rendered":"R\uc758 lm() \ud568\uc218\uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218\ub97c \ucd94\ucd9c\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

<\/p>\n

\n

\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec R\uc758 lm() \ud568\uc218<\/a> \uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218\ub97c \ucd94\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ubc29\ubc95 1: \ud68c\uadc0\uacc4\uc218\ub9cc \ucd94\ucd9c<\/strong><\/span><\/p>\n

 model$coefficients\n<\/strong><\/pre>\n
 \ubc29\ubc95 2: \ud45c\uc900 \uc624\ucc28, T \ud1b5\uacc4 \ubc0f P \uac12\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud68c\uadc0 \uacc4\uc218 \ucd94\ucd9c<\/strong><\/span><\/p>\n
 summary(model)$coefficients<\/strong><\/pre>\n
 \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 \uc608: R\uc758 lm()\uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218 \ucd94\ucd9c<\/strong><\/span><\/h3>\n
 R\uc5d0 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\ud569\ud558\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (rating=c(67, 75, 79, 85, 90, 96, 97),\n                 points=c(8, 12, 16, 15, 22, 28, 24),\n                 assists=c(4, 6, 6, 5, 3, 8, 7),\n                 rebounds=c(1, 4, 3, 3, 2, 6, 7))\n\n#fit multiple linear regression model\n<\/span>model <- lm(rating ~ points + assists + rebounds, data=df)\n<\/strong><\/pre>\n
 summary()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud68c\uadc0 \ubaa8\ub378\uc758 \uc804\uccb4 \uc694\uc57d\uc744 \ud45c\uc2dc\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 #view model summary\n<\/span>summary(model)\n\nCall:\nlm(formula = rating ~ points + assists + rebounds, data = df)\n\nResiduals:\n      1 2 3 4 5 6 7 \n-1.5902 -1.7181 0.2413 4.8597 -1.0201 -0.6082 -0.1644 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)   \n(Intercept) 66.4355 6.6932 9.926 0.00218 **\npoints 1.2152 0.2788 4.359 0.02232 * \nassists -2.5968 1.6263 -1.597 0.20860   \nrebounds 2.8202 1.6118 1.750 0.17847   \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 3.193 on 3 degrees of freedom\nMultiple R-squared: 0.9589, Adjusted R-squared: 0.9179 \nF-statistic: 23.35 on 3 and 3 DF, p-value: 0.01396\n<\/strong><\/pre>\n
 \ud68c\uadc0 \uacc4\uc218\ub9cc \ud45c\uc2dc\ud558\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 model$ \uacc4\uc218\ub97c<\/strong> \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #view only regression coefficients of model\nmodel$coefficients\n\n(Intercept) points assists rebounds \n  66.435519 1.215203 -2.596789 2.820224<\/span><\/span>\n<\/strong><\/pre>\n
 \uc774\ub7ec\ud55c \uacc4\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc74c\uacfc \uac19\uc740 \uc801\ud569 \ud68c\uadc0 \ubc29\uc815\uc2dd\uc744 \uc791\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc810\uc218 = 66.43551 + 1.21520(\ud3ec\uc778\ud2b8) \u2013 2.59678(\uc5b4\uc2dc\uc2a4\ud2b8) + 2.82022(\ub9ac\ubc14\uc6b4\ub4dc)<\/span><\/p>\n
 \ud45c\uc900 \uc624\ub958, t-\ud1b5\uacc4 \ubc0f p-\uac12\uacfc \ud568\uaed8 \ud68c\uadc0 \uacc4\uc218\ub97c \ud45c\uc2dc\ud558\ub824\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 summary(model)$ \uacc4\uc218\ub97c<\/strong> \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #view regression coefficients with standard errors, t-statistics, and p-values\n<\/span>summary(model)$coefficients\n\n             Estimate Std. Error t value Pr(>|t|)\n(Intercept) 66.435519 6.6931808 9.925852 0.002175313\npoints 1.215203 0.2787838 4.358942 0.022315418\nassists -2.596789 1.6262899 -1.596757 0.208600183\nrebounds 2.820224 1.6117911 1.749745 0.178471275<\/strong><\/pre>\n
 \uc774 \ucd9c\ub825\uc5d0\uc11c \ud2b9\uc815 \uac12\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 \uc608\ub97c \ub4e4\uc5b4, \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec points<\/strong> \ubcc0\uc218\uc758 p \uac12<\/strong> \uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #view p-value for points variable\n<\/span>summary(model)$coefficients[\" points<\/span> \", \" Pr(>|t|)<\/span> \"]\n\n[1] 0.02231542\n<\/strong><\/pre>\n
 \ub610\ub294 \ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac01 \ud68c\uadc0 \uacc4\uc218\uc5d0 \ub300\ud55c p-\uac12\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 #view p-value for all variables\n<\/span>summary(model)$coefficients[, \" Pr(>|t|)<\/span> \"]\n\n(Intercept) points assists rebounds \n0.002175313 0.022315418 0.208600183 0.178471275 \n<\/strong><\/pre>\n
 \ubaa8\ub378\uc758 \uac01 \ud68c\uadc0\uacc4\uc218\uc5d0 \ub300\ud55c P\uac12\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 \uc720\uc0ac\ud55c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud68c\uadc0 \ucd9c\ub825\uc758 \ubaa8\ub4e0 \uac12\uc5d0 \uc561\uc138\uc2a4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 R\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 R\uc5d0\uc11c \ub2e8\uc21c \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \uc794\ucc28 \ud50c\ub86f\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\ub2e4\uc74c \ubc29\ubc95\uc744 \uc0ac\uc6a9\ud558\uc5ec R\uc758 lm() \ud568\uc218 \uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218\ub97c \ucd94\ucd9c\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubc29\ubc95 1: \ud68c\uadc0\uacc4\uc218\ub9cc \ucd94\ucd9c model$coefficients \ubc29\ubc95 2: \ud45c\uc900 \uc624\ucc28, T \ud1b5\uacc4 \ubc0f P \uac12\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud68c\uadc0 \uacc4\uc218 \ucd94\ucd9c summary(model)$coefficients \ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \ubc29\ubc95\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. \uc608: R\uc758 lm()\uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218 \ucd94\ucd9c R\uc5d0 \ub2e4\uc74c\uacfc \uac19\uc740 \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\ud569\ud558\ub2e4\uace0 \uac00\uc815\ud569\ub2c8\ub2e4. #create […]<\/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-2945","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nR\uc758 lm() \ud568\uc218\uc5d0\uc11c \ud68c\uadc0 \uacc4\uc218\ub97c \ucd94\ucd9c\ud558\ub294 \ubc29\ubc95 - 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