{"id":938,"date":"2023-07-28T06:10:31","date_gmt":"2023-07-28T06:10:31","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%9a%e1%80%af%e1%80%b6%e1%80%80%e1%80%bc%e1%80%8a%e1%80%ba%e1%80%99%e1%80%be%e1%80%af%e1%80%80%e1%80%bc%e1%80%ac%e1%80%b8%e1%80%80%e1%80%ac%e1%80%9c-r-%e1%80%80%e1%80%ad%e1%80%af%e1%80%86\/"},"modified":"2023-07-28T06:10:31","modified_gmt":"2023-07-28T06:10:31","slug":"%e1%80%9a%e1%80%af%e1%80%b6%e1%80%80%e1%80%bc%e1%80%8a%e1%80%ba%e1%80%99%e1%80%be%e1%80%af%e1%80%80%e1%80%bc%e1%80%ac%e1%80%b8%e1%80%80%e1%80%ac%e1%80%9c-r-%e1%80%80%e1%80%ad%e1%80%af%e1%80%86","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/%e1%80%9a%e1%80%af%e1%80%b6%e1%80%80%e1%80%bc%e1%80%8a%e1%80%ba%e1%80%99%e1%80%be%e1%80%af%e1%80%80%e1%80%bc%e1%80%ac%e1%80%b8%e1%80%80%e1%80%ac%e1%80%9c-r-%e1%80%80%e1%80%ad%e1%80%af%e1%80%86\/","title":{"rendered":"R \u1010\u103d\u1004\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u103d\u1032\u1019\u100a\u103a\u1014\u100a\u103a\u1038\u104b"},"content":{"rendered":"

<\/p>\n

\n

\u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c<\/a> \u101e\u100a\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1005\u102d\u1010\u103a\u1001\u103b\u1019\u103e\u102f\u1021\u1006\u1004\u1037\u103a\u1010\u1005\u103a\u1001\u102f\u101b\u103e\u102d \u101c\u1030\u1026\u1038\u101b\u1031\u1000\u1014\u1037\u103a\u101e\u1010\u103a\u1001\u103b\u1000\u103a\u1015\u102b\u1040\u1004\u103a\u1014\u102d\u102f\u1004\u103a\u1001\u103c\u1031\u101b\u103e\u102d\u101e\u1031\u102c \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1021\u1000\u103d\u102c\u1021\u101d\u1031\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u101e\u100a\u103a R \u1010\u103d\u1004\u103a \u1012\u1031\u1010\u102c\u1021\u1010\u103d\u1032\u1010\u1005\u103a\u1001\u102f\u1021\u1010\u103d\u1000\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u103d\u1032\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1025\u1015\u1019\u102c- R \u1010\u103d\u1004\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1015\u102f\u1036\u1016\u1031\u102c\u103a\u1001\u103c\u1004\u103a\u1038\u104b<\/strong><\/h3>\n

R \u1010\u103d\u1004\u103a \u1021\u1010\u1014\u103a\u1038 100 \u1014\u103e\u1004\u1037\u103a \u1000\u1031\u102c\u103a\u101c\u1036 2 \u1001\u102f\u1015\u102b\u101e\u1031\u102c \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1012\u1031\u1010\u102c\u1021\u1005\u102f\u1036\u101b\u103e\u102d\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b<\/span><\/p>\n

 #make this example reproducible<\/span>\nset.seed(0)\n\n#create dataset<\/span>\nx <- rnorm(100)\ny <- x*2 + rnorm(100)\ndf <- data.frame(x = x, y = y)\n\n#view first six rows of dataset<\/span>\nhead(df)\n\n           xy\n1 1.2629543 3.3077678\n2 -0.3262334 -1.4292433\n3 1.3297993 2.0436086\n4 1.2724293 2.5914389\n5 0.4146414 -0.3011029\n6 -1.5399500 -2.5031813\n<\/strong><\/pre>\n
 x \u1014\u103e\u1004\u1037\u103a y \u1021\u1000\u103c\u102c\u1038 \u1006\u1000\u103a\u1014\u103d\u101a\u103a\u1019\u103e\u102f\u104f \u1002\u101b\u1015\u103a\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a\u104a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u101e\u100a\u103a \u1015\u1011\u1019\u1026\u1038\u1005\u103d\u102c linear regression model \u1000\u102d\u102f \u1000\u102d\u102f\u1000\u103a\u100a\u102e\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 model <- lm(y ~ x, data = df)\n<\/strong><\/pre>\n
 \u1011\u102d\u102f\u1037\u1014\u1031\u102c\u1000\u103a\u104a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u101e\u100a\u103a abline()<\/a> \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1014\u103e\u1004\u1037\u103a \u1021\u1019\u103e\u1014\u103a\u1010\u1000\u101a\u103a\u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102d\u102f\u1038\u101d\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u101b\u1014\u103a\u1021\u1010\u103d\u1000\u103a abline() \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1014\u103e\u1004\u1037\u103a \u101c\u102d\u102f\u1004\u103a\u1038\u1019\u103b\u102c\u1038() \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u1001\u1014\u1037\u103a\u1019\u103e\u1014\u103a\u1038\u1001\u103c\u1031\u1019\u103b\u1009\u103a\u1038\u1006\u102f\u1010\u103a\u1006\u102f\u1010\u103a\u1019\u103b\u1009\u103a\u1038\u1010\u1005\u103a\u1000\u103d\u1000\u103a\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span> <\/p>\n
 #get predicted y values using regression equation<\/span>\nnewx <- seq(min(df$x), max(df$x), length.out=100)\npreds <- predict(model, newdata = data.frame(x=newx), interval = 'confidence')\n\n#create plot of x vs. y, but don't display individual points (type='n')<\/span> \nplot(y ~ x, data = df, type = 'n')\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong> <\/pre>\n
\"R<\/p>\n
 \u1021\u1014\u1000\u103a\u101b\u1031\u102c\u1004\u103a\u1019\u103b\u1009\u103a\u1038\u101e\u100a\u103a \u1010\u1015\u103a\u1006\u1004\u103a\u1011\u102c\u1038\u101e\u1031\u102c \u1019\u103b\u1009\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1021\u1010\u102d\u102f\u1004\u103a\u1038 \u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1019\u103b\u1009\u103a\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u1015\u103c\u102e\u1038 \u1021\u1015\u103c\u102c\u101b\u1031\u102c\u1004\u103a\u1019\u103b\u1009\u103a\u1038\u1014\u103e\u1005\u103a\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u101e\u100a\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u103a\u104b<\/span><\/p>\n
 \u1005\u102d\u1010\u103a\u1000\u103c\u102d\u102f\u1000\u103a\u101b\u103d\u1031\u1038\u1001\u103b\u101a\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104a \u101e\u1004\u103a\u101e\u100a\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1000\u102f\u1012\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1019\u103b\u1025\u103a\u1038\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a \u1001\u1014\u1037\u103a\u1019\u103e\u1014\u103a\u1038\u1001\u103c\u1031\u1019\u103b\u1009\u103a\u1038\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1006\u102f\u1010\u103a\u101a\u102f\u1010\u103a\u1019\u103e\u102f\u1019\u103b\u1009\u103a\u1038\u1000\u103c\u102c\u1038\u101b\u103e\u102d \u1027\u101b\u102d\u101a\u102c\u1000\u102d\u102f\u101c\u100a\u103a\u1038 \u1016\u103c\u100a\u1037\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span> <\/p>\n
 #create plot of x vs. y<\/span>\nplot(y ~ x, data = df, type = 'n')\n\n#fill in area between regression line and confidence interval\npolygon(c(rev(newx), newx), c(rev(preds[,3]), preds[,2]), col = 'grey', border = NA)<\/span>\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong> <\/pre>\n
\"R<\/p>\n
 \u1024\u1010\u103d\u1004\u103a \u1000\u102f\u1012\u103a\u1021\u1015\u103c\u100a\u1037\u103a\u1021\u1005\u102f\u1036\u1019\u103e\u102c \u1021\u1005\u1019\u103e\u1021\u1006\u102f\u1036\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n
 #make this example reproducible\nset.seed(0)<\/span>\n\n#create dataset\nx <- rnorm(100)<\/span>\ny <- x*2 + rnorm(100)<\/span>\ndf <- data.frame(x = x, y = y)<\/span>\n\n#fit linear regression model\nmodel <- lm(y ~ x, data = df)<\/span>\n\n#get predicted y values using regression equation\nnewx <- seq(min(df$x), max(df$x), length.out=100)<\/span>\npreds <- predict(model, newdata = data.frame(x=newx), interval = 'confidence')<\/span>\n\n#create plot of x vs. y<\/span>\nplot(y ~ x, data = df, type = 'n')\n\n#fill in area between regression line and confidence interval\npolygon(c(rev(newx), newx), c(rev(preds[,3]), preds[,2]), col = 'grey', border = NA)<\/span>\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong><\/pre>\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><\/h3>\n
 \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1006\u102d\u102f\u1010\u102c \u1018\u102c\u101c\u1032\u104b<\/a>
 \u1000\u103d\u1000\u103a\u1019\u103b\u102c\u1038\u101e\u102d\u102f\u1037 \u1019\u103b\u1009\u103a\u1038\u1016\u103c\u1031\u102c\u1004\u1037\u103a\u1019\u103b\u102c\u1038\u1011\u100a\u1037\u103a\u101b\u1014\u103a R \u1010\u103d\u1004\u103a abline() \u101c\u102f\u1015\u103a\u1006\u1031\u102c\u1004\u103a\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101b\u1019\u100a\u103a\u1014\u100a\u103a\u1038\u104b<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c \u101e\u100a\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1005\u102d\u1010\u103a\u1001\u103b\u1019\u103e\u102f\u1021\u1006\u1004\u1037\u103a\u1010\u1005\u103a\u1001\u102f\u101b\u103e\u102d \u101c\u1030\u1026\u1038\u101b\u1031\u1000\u1014\u1037\u103a\u101e\u1010\u103a\u1001\u103b\u1000\u103a\u1015\u102b\u1040\u1004\u103a\u1014\u102d\u102f\u1004\u103a\u1001\u103c\u1031\u101b\u103e\u102d\u101e\u1031\u102c \u1010\u1014\u103a\u1016\u102d\u102f\u1038\u1019\u103b\u102c\u1038\u1021\u1000\u103d\u102c\u1021\u101d\u1031\u1038\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b \u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u101e\u100a\u103a R \u1010\u103d\u1004\u103a \u1012\u1031\u1010\u102c\u1021\u1010\u103d\u1032\u1010\u1005\u103a\u1001\u102f\u1021\u1010\u103d\u1000\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u103d\u1032\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c- R \u1010\u103d\u1004\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1015\u102f\u1036\u1016\u1031\u102c\u103a\u1001\u103c\u1004\u103a\u1038\u104b R \u1010\u103d\u1004\u103a \u1021\u1010\u1014\u103a\u1038 100 \u1014\u103e\u1004\u1037\u103a \u1000\u1031\u102c\u103a\u101c\u1036 2 \u1001\u102f\u1015\u102b\u101e\u1031\u102c \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1012\u1031\u1010\u102c\u1021\u1005\u102f\u1036\u101b\u103e\u102d\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b #make this example reproducible set.seed(0) #create dataset x <- rnorm(100) y <- x*2 + rnorm(100) df <- data.frame(x = x, y = y) #view first six rows of dataset […]<\/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 \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u103d\u1032\u1019\u100a\u103a\u1014\u100a\u103a\u1038\u104b<\/title>\n<meta name=\"description\" content=\"R \u1010\u103d\u1004\u103a \u101a\u102f\u1036\u1000\u103c\u100a\u103a\u1019\u103e\u102f\u1000\u103c\u102c\u1038\u1000\u102c\u101c\u1000\u102d\u102f \u1019\u100a\u103a\u101e\u102d\u102f\u1037\u1006\u103d\u1032\u101b\u1019\u100a\u103a\u1000\u102d\u102f \u1025\u1015\u1019\u102c\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1004\u1037\u103a 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