{"id":3662,"date":"2023-07-16T06:46:06","date_gmt":"2023-07-16T06:46:06","guid":{"rendered":"https:\/\/statorials.org\/my\/rmse-%e1%80%80%e1%80%ad%e1%80%af-lm-in-r-%e1%80%99%e1%80%be-%e1%80%91%e1%80%af%e1%80%90%e1%80%ba%e1%80%9a%e1%80%b0%e1%80%95%e1%80%ab%e1%81%8b\/"},"modified":"2023-07-16T06:46:06","modified_gmt":"2023-07-16T06:46:06","slug":"rmse-%e1%80%80%e1%80%ad%e1%80%af-lm-in-r-%e1%80%99%e1%80%be-%e1%80%91%e1%80%af%e1%80%90%e1%80%ba%e1%80%9a%e1%80%b0%e1%80%95%e1%80%ab%e1%81%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/rmse-%e1%80%80%e1%80%ad%e1%80%af-lm-in-r-%e1%80%99%e1%80%be-%e1%80%91%e1%80%af%e1%80%90%e1%80%ba%e1%80%9a%e1%80%b0%e1%80%95%e1%80%ab%e1%81%8b\/","title":{"rendered":"R \u1010\u103d\u1004\u103a lm() function \u1019\u103e rmse \u1000\u102d\u102f\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1011\u102f\u1010\u103a\u101a\u1030\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

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R \u1010\u103d\u1004\u103a lm()<\/a> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u104f root mean square error (RMSE) \u1000\u102d\u102f<\/strong> \u1011\u102f\u1010\u103a\u101a\u1030\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \u1000\u102d\u102f \u101e\u1004\u103a\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

 sqrt(mean(model$residuals^2))\n<\/strong><\/pre>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1025\u1015\u1019\u102c\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1015\u103c\u101e\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1006\u1000\u103a\u1005\u1015\u103a-<\/strong> Root Mean Square Error (RMSE) \u1000\u102d\u102f \u1018\u101a\u103a\u101c\u102d\u102f\u1021\u1013\u102d\u1015\u1039\u1015\u102c\u101a\u103a\u1016\u103d\u1004\u1037\u103a\u1019\u101c\u1032<\/a><\/span><\/p>\n
 \u1025\u1015\u1019\u102c- R \u1016\u103c\u1004\u1037\u103a lm() \u1019\u103e RMSE \u1000\u102d\u102f \u1011\u102f\u1010\u103a\u101a\u1030\u1015\u102b\u104b<\/strong><\/span><\/h2>\n
 R \u1010\u103d\u1004\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b multiple linear regression model \u1014\u103e\u1004\u1037\u103a \u1000\u102d\u102f\u1000\u103a\u100a\u102e\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b<\/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
 \u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1015\u102f\u1036\u1005\u1036\u104f \u1021\u1000\u103b\u1009\u103a\u1038\u1001\u103b\u102f\u1015\u103a\u1021\u1015\u103c\u100a\u1037\u103a\u1021\u1005\u102f\u1036\u1000\u102d\u102f\u1015\u103c\u101e\u101b\u1014\u103a summary()<\/strong> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/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
 \u1019\u1031\u102c\u103a\u1012\u101a\u103a\u104f root mean square error (RMSE) \u1000\u102d\u102f\u101e\u102c \u1011\u102f\u1010\u103a\u101a\u1030\u101b\u1014\u103a\u104a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u1014\u102d\u102f\u1004\u103a\u1015\u102b\u101e\u100a\u103a\u104b<\/span><\/p>\n
 #extract RMSE of regression model\nsqrt(mean(model$residuals^2))\n\n[1] 2.090564\n<\/span><\/span><\/strong><\/pre>\n
 \u1019\u1031\u102c\u103a\u1012\u101a\u103a\u104f RMSE \u101e\u100a\u103a 2.090564<\/strong> \u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u104e\u1004\u103a\u1038\u101e\u100a\u103a \u1019\u1031\u102c\u103a\u1012\u101a\u103a\u104f \u1001\u1014\u1037\u103a\u1019\u103e\u1014\u103a\u1038\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a \u1012\u1031\u1010\u102c\u1021\u1010\u103d\u1032\u104f \u1021\u1019\u103e\u1014\u103a\u1010\u1000\u101a\u103a\u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1021\u1000\u103c\u102c\u1038 \u1015\u103b\u1019\u103a\u1038\u1019\u103b\u103e\u1021\u1000\u103d\u102c\u1021\u101d\u1031\u1038\u1000\u102d\u102f \u1000\u102d\u102f\u101a\u103a\u1005\u102c\u1038\u1015\u103c\u102f\u101e\u100a\u103a\u104b<\/span><\/p>\n
 RMSE \u1014\u102d\u1019\u1037\u103a\u101c\u1031\u104a \u1015\u1031\u1038\u1011\u102c\u1038\u101e\u1031\u102c \u1019\u1031\u102c\u103a\u1012\u101a\u103a\u101e\u100a\u103a \u1012\u1031\u1010\u102c\u1021\u1005\u102f\u1036\u1000\u102d\u102f \u201c\u1021\u1036\u1000\u102d\u102f\u1000\u103a\u201d \u101c\u102f\u1015\u103a\u1014\u102d\u102f\u1004\u103a\u101c\u1031\u101c\u1031 \u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1019\u1010\u1030\u100a\u102e\u101e\u1031\u102c \u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1015\u102f\u1036\u1005\u1036\u1019\u103b\u102c\u1038 \u1021\u1019\u103b\u102c\u1038\u1021\u1015\u103c\u102c\u1038\u1000\u102d\u102f \u1014\u103e\u102d\u102f\u1004\u103a\u1038\u101a\u103e\u1009\u103a\u101e\u1031\u102c\u1021\u1001\u102b\u104a \u1021\u1014\u102d\u1019\u1037\u103a\u1006\u102f\u1036\u1038 RMSE \u1014\u103e\u1004\u1037\u103a \u1019\u1031\u102c\u103a\u1012\u101a\u103a\u1000\u102d\u102f \u1012\u1031\u1010\u102c\u1021\u1005\u102f\u1036\u101c\u102d\u102f\u1000\u103a “ \u1021\u1036\u1000\u102d\u102f\u1000\u103a”  \u1021\u1000\u1031\u102c\u1004\u103a\u1038\u1006\u102f\u1036\u1038\u101f\u102f \u101e\u1010\u103a\u1019\u103e\u1010\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1011\u1015\u103a\u101c\u1031\u102c\u1004\u103a\u1038\u1021\u101b\u1004\u103a\u1038\u1021\u1019\u103c\u1005\u103a\u1019\u103b\u102c\u1038<\/strong><\/span><\/h2>\n
 \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1019\u103b\u102c\u1038\u101e\u100a\u103a R \u1010\u103d\u1004\u103a \u1021\u1001\u103c\u102c\u1038\u1018\u102f\u1036\u1021\u101c\u102f\u1015\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u101e\u100a\u103a-<\/span><\/p>\n
 R \u1010\u103d\u1004\u103a \u101b\u102d\u102f\u1038\u101b\u103e\u1004\u103a\u1038\u101e\u1031\u102c linear regression \u101c\u102f\u1015\u103a\u1014\u100a\u103a\u1038<\/a>
 R \u1010\u103d\u1004\u103a linear regression \u1021\u1019\u103b\u102c\u1038\u1021\u1015\u103c\u102c\u1038\u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1014\u100a\u103a\u1038<\/a>
 R \u1010\u103d\u1004\u103a\u1000\u103b\u1014\u103a\u101b\u103e\u102d\u101e\u1031\u102c\u1000\u103d\u1000\u103a\u1000\u103d\u1000\u103a\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
R \u1010\u103d\u1004\u103a lm() \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u104f root mean square error (RMSE) \u1000\u102d\u102f \u1011\u102f\u1010\u103a\u101a\u1030\u101b\u1014\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b syntax \u1000\u102d\u102f \u101e\u1004\u103a\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b sqrt(mean(model$residuals^2)) \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1025\u1015\u1019\u102c\u101e\u100a\u103a \u1024 syntax \u1000\u102d\u102f \u101c\u1000\u103a\u1010\u103d\u1031\u1037\u1010\u103d\u1004\u103a \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1015\u103c\u101e\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1006\u1000\u103a\u1005\u1015\u103a- Root Mean Square Error (RMSE) \u1000\u102d\u102f \u1018\u101a\u103a\u101c\u102d\u102f\u1021\u1013\u102d\u1015\u1039\u1015\u102c\u101a\u103a\u1016\u103d\u1004\u1037\u103a\u1019\u101c\u1032 \u1025\u1015\u1019\u102c- R \u1016\u103c\u1004\u1037\u103a lm() \u1019\u103e RMSE \u1000\u102d\u102f \u1011\u102f\u1010\u103a\u101a\u1030\u1015\u102b\u104b R \u1010\u103d\u1004\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b multiple linear regression model \u1014\u103e\u1004\u1037\u103a \u1000\u102d\u102f\u1000\u103a\u100a\u102e\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b #create data frame df <- data. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"\nR - Statology \u1010\u103d\u1004\u103a lm() \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1019\u103e RMSE \u1000\u102d\u102f\u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1011\u102f\u1010\u103a\u101a\u1030\u1014\u100a\u103a\u1038<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a \u1025\u1015\u1019\u102c\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1004\u1037\u103a R in regression model \u1021\u1010\u103d\u1000\u103a lm() function \u1019\u103e RMSE \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1011\u102f\u1010\u103a\u101a\u1030\u101b\u1019\u100a\u103a\u1000\u102d\u102f 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\u1025\u1015\u1019\u102c\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1004\u1037\u103a R in regression model \u1021\u1010\u103d\u1000\u103a lm() function \u1019\u103e RMSE \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1011\u102f\u1010\u103a\u101a\u1030\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/my\/rmse-\u1000\u102d\u102f-lm-in-r-\u1019\u103e-\u1011\u102f\u1010\u103a\u101a\u1030\u1015\u102b\u104b\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-16T06:46:06+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin Anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin 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