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Data X:
59 2.110 59 65 36 134 109 92 88 33 21 61 101 75 37 83 46 64 61 21 49 158 93 47 44 82 52 69 84 59 42 37 79 76 144 178 380 87 56 54 36 75 89 51 7 78 79 31 158 30 115 31 57 62 47 41 69 47 37 154 49 48 44 45 37 150 27 35 100 63 398 127 88 797 212 147 206 109 386 219 86 534 204 133 676 303 95 226 124 96 67 7 122 34 26 99 118 25 34 45 39 37 55 43 48 59 44 57 17 102 31 47 144 72 69 32 22 39 13 23 52 39 27 48 117 40 30 28 42 47 34 99 26 45 80 23 37 31 41 17 74 68 569 52 39 55 49 145 62 43 31 97 35 19 15 130 38 48 40 71 49 19 28 50 20 32 119 29 68 94 25 87 135 17 13 49 37 140 16 38 23 63 75 474 43 52 97 102 89 8 116 60 44 36 53 17 149 10 89 57 51 40 28 10 45 35 41 109 299 44 18 138 152 142 94 9 86 42 55 48 297 42 40 40 30 126 35 44 36 253 36 18 47 26 38 28 69 44 58 37 24 34 66 48 50 355 81 106 64 70 68 137 29 76 74 57 40 181 85 49 84 46 100 40 86 57 86 21 75 30 64 85 110 35 47 157 50 1.105 22 86 29 38 79 24 34 55 36 39 31 30 40 57 31 139 104 28 44 23 17 6 20 24 27 181 65 155 73 338 77 110 115 55 45 7 19 21 12 56 57 774 126 140 43 104 61 50 76 30 68 35 51 23 67 48 72 19 35 16 384 68 23 69 63 14 20 180 60 62 48 263 63 34 23 81 33 48 27 105 27 41 9 21 17 17 55 31 52 61 18 37 18 38 13 55 19 223 20 51 12 62 10 19 19 11 14 98 21 15 21 9 9 15 42 17 18 5 129 31 39 29 47 72 23 23 44 55 128 23 804 88 87 245 59 50 64 70 52 105 34 26 16 13 16 21 11 55 73 50 45 45 13 24 26 36 11 40 43 27 42 31 20 37 209 26 35 11 20 31 21 11 22 5 9 13 8 55 15 20 19 27 59 13 7 40 178 73 255 37 34 342 51 68 51 23 59 170 92 86 27 48 121 53 77 44 128 102 62 64 72 51 58 111 50 68 42 149 28 39 1 40 30 115 68 114 37 157 11 144 19 81 11 38 59 11 16 21 20 16 17 13 35 7 20 16 57 19 9 17 12 42 22 5 5 23 12 41 27 19 9 10 49 30 22 18 8 14 6 22 45 36 10 24 35 15 59 57 14 26 23 15 12 43 14 40 20 7 110 23 55 19 34 21 56 457 14 36 25 110 32 83 34 113 12 39 7 43 25 61 18
Data Y:
32 1.106 15 51 30 94 46 62 33 19 15 33 57 50 16 58 19 38 28 14 45 84 42 18 35 42 25 48 42 18 34 24 51 45 101 84 206 45 34 35 14 45 65 28 2 49 39 22 72 21 76 20 45 34 27 37 35 26 13 59 25 22 33 29 30 117 17 25 47 47 230 69 32 4.600 122 105 113 67 270 126 43 254 144 112 412 179 75 119 101 71 30 3 72 22 24 76 98 6 20 23 23 21 36 29 35 40 30 29 3 62 29 30 96 37 40 27 13 24 11 20 39 26 27 23 74 27 14 16 15 24 14 73 12 25 40 10 18 16 27 14 36 29 255 29 15 36 28 95 25 21 10 55 26 12 15 89 26 18 20 40 27 7 20 33 12 24 86 21 62 53 22 52 67 18 7 37 21 71 20 28 16 37 45 360 35 26 54 54 55 7 87 28 21 21 31 1 86 6 68 47 33 21 16 8 19 19 33 72 217 31 10 91 87 73 57 4 43 32 39 48 239 24 23 23 25 75 25 19 28 127 35 17 25 18 22 15 51 30 31 27 14 24 62 28 25 210 36 81 39 36 38 88 19 71 47 38 28 130 73 22 52 31 58 37 56 33 67 14 59 11 34 44 79 18 47 75 23 664 19 35 20 39 57 21 23 20 37 18 16 16 26 30 11 63 68 14 26 16 8 5 14 15 14 100 35 86 39 217 35 62 69 39 33 14 19 19 9 23 49 782 117 97 31 58 49 31 68 28 29 34 28 13 61 57 65 15 35 8 293 52 18 65 68 14 22 154 44 56 37 234 53 17 8 52 37 29 18 107 23 27 7 16 13 11 42 25 43 47 13 26 13 28 12 57 10 206 22 29 8 41 3 7 13 12 8 76 15 9 12 4 10 23 38 5 21 6 90 28 42 29 31 72 6 19 44 55 146 19 812 73 71 255 64 29 25 58 35 95 26 32 7 11 7 6 11 45 49 43 19 27 17 8 13 36 16 26 21 17 39 20 5 29 200 14 30 10 6 24 14 9 16 9 6 4 5 36 1 10 11 19 44 7 11 24 101 55 179 15 28 239 28 45 33 14 20 110 50 52 14 18 65 26 26 27 71 53 27 41 37 28 31 72 34 58 24 63 22 13 0 29 13 69 30 81 13 108 7 99 5 42 5 15 40 4 5 14 29 8 19 0 32 10 16 13 63 13 9 4 13 33 19 0 6 12 15 22 14 15 10 7 25 18 10 14 11 14 6 10 30 18 6 21 24 12 41 48 14 19 13 11 5 40 14 18 9 10 96 14 28 21 25 22 30 343 15 24 25 109 17 72 23 53 24 26 5 45 27 46 15
Sample Range:
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To:
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Label x-axis:
R Code
par1 <- as.numeric(par1) library(lattice) z <- as.data.frame(cbind(x,y)) m <- lm(y~x) summary(m) bitmap(file='test1.png') plot(z,main='Scatterplot, lowess, and regression line') lines(lowess(z),col='red') abline(m) grid() dev.off() bitmap(file='test2.png') m2 <- lm(m$fitted.values ~ x) summary(m2) z2 <- as.data.frame(cbind(x,m$fitted.values)) names(z2) <- list('x','Fitted') plot(z2,main='Scatterplot, lowess, and regression line') lines(lowess(z2),col='red') abline(m2) grid() dev.off() bitmap(file='test3.png') m3 <- lm(m$residuals ~ x) summary(m3) z3 <- as.data.frame(cbind(x,m$residuals)) names(z3) <- list('x','Residuals') plot(z3,main='Scatterplot, lowess, and regression line') lines(lowess(z3),col='red') abline(m3) grid() dev.off() bitmap(file='test4.png') m4 <- lm(m$fitted.values ~ m$residuals) summary(m4) z4 <- as.data.frame(cbind(m$residuals,m$fitted.values)) names(z4) <- list('Residuals','Fitted') plot(z4,main='Scatterplot, lowess, and regression line') lines(lowess(z4),col='red') abline(m4) grid() dev.off() bitmap(file='test5.png') myr <- as.ts(m$residuals) z5 <- as.data.frame(cbind(lag(myr,1),myr)) names(z5) <- list('Lagged Residuals','Residuals') plot(z5,main='Lag plot') m5 <- lm(z5) summary(m5) abline(m5) grid() dev.off() bitmap(file='test6.png') hist(m$residuals,main='Residual Histogram',xlab='Residuals') dev.off() bitmap(file='test7.png') if (par1 > 0) { densityplot(~m$residuals,col='black',main=paste('Density Plot bw = ',par1),bw=par1) } else { densityplot(~m$residuals,col='black',main='Density Plot') } dev.off() bitmap(file='test8.png') acf(m$residuals,main='Residual Autocorrelation Function') dev.off() bitmap(file='test9.png') qqnorm(x) qqline(x) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Simple Linear Regression',5,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Statistics',1,TRUE) a<-table.element(a,'Estimate',1,TRUE) a<-table.element(a,'S.D.',1,TRUE) a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE) a<-table.element(a,'P-value (two-sided)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'constant term',header=TRUE) a<-table.element(a,m$coefficients[[1]]) sd <- sqrt(vcov(m)[1,1]) a<-table.element(a,sd) tstat <- m$coefficients[[1]]/sd a<-table.element(a,tstat) pval <- 2*(1-pt(abs(tstat),length(x)-2)) a<-table.element(a,pval) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'slope',header=TRUE) a<-table.element(a,m$coefficients[[2]]) sd <- sqrt(vcov(m)[2,2]) a<-table.element(a,sd) tstat <- m$coefficients[[2]]/sd a<-table.element(a,tstat) pval <- 2*(1-pt(abs(tstat),length(x)-2)) a<-table.element(a,pval) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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