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Data X:
87.28 87.28 87.09 86.92 87.59 90.72 90.69 90.3 89.55 88.94 88.41 87.82 87.07 86.82 86.4 86.02 85.66 85.32 85 84.67 83.94 82.83 81.95 81.19 80.48 78.86 69.47 68.77 70.06 73.95 75.8 77.79 81.57 83.07 84.34 85.1 85.25 84.26 83.63 86.44 85.3 84.1 83.36 82.48 81.58 80.47 79.34 82.13 81.69 80.7 79.88 79.16 78.38 77.42 76.47 75.46 74.48 78.27 80.7 79.91 78.75 77.78 81.14 81.08 80.03 78.91 78.01 76.9 75.97 81.93 80.27 78.67 77.42 76.16 74.7 76.39 76.04 74.65 73.29 71.79 74.39 74.91 74.54 73.08 72.75 71.32 70.38 70.35 70.01 69.36 67.77 69.26 69.8 68.38 67.62 68.39 66.95 65.21 66.64 63.45 60.66 62.34 60.32 58.64 60.46 58.59 61.87 61.85 67.44 77.06 91.74 93.15 94.15 93.11 91.51 89.96 88.16 86.98 88.03 86.24 84.65 83.23 81.7 80.25 78.8 77.51 76.2 75.04 74 75.49 77.14 76.15 76.27 78.19 76.49 77.31 76.65 74.99 73.51 72.07 70.59 71.96 76.29 74.86 74.93 71.9 71.01 77.47 75.78 76.6 76.07 74.57 73.02 72.65 73.16 71.53 69.78 67.98 69.96 72.16 70.47 68.86 67.37 65.87 72.16 71.34 69.93 68.44 67.16 66.01 67.25 70.91 69.75 68.59 67.48 66.31 64.81 66.58 65.97 64.7 64.7 60.94 59.08 58.42 57.77 57.11 53.31 49.96 49.4 48.84 48.3 47.74 47.24 46.76 46.29 48.9 49.23 48.53 48.03 54.34 53.79 53.24 52.96 52.17 51.7 58.55 78.2 77.03 76.19 77.15 75.87 95.47 109.67 112.28 112.01 107.93 105.96 105.06 102.98 102.2 105.23 101.85 99.89 96.23 94.76 91.51 91.63 91.54 85.23 87.83 87.38 84.44 85.19 84.03 86.73 102.52 104.45 106.98 107.02 99.26 94.45 113.44 157.33 147.38 171.89 171.95 132.71 126.02 121.18 115.45 110.48 117.85 117.63 124.65 109.59 111.27 99.78 98.21 99.2 97.97 89.55 87.91 93.34 94.42 93.2 90.29 91.46 89.98 88.35 88.41 82.44 79.89 75.69 75.66 84.5 96.73 87.48 82.39 83.48 79.31 78.16 72.77 72.45 68.46 67.62 68.76 70.07 68.55 65.3 58.96 59.17 62.37 66.28 55.62 55.23 55.85 56.75 50.89 53.88 52.95 55.08 53.61 58.78 61.85 55.91 53.32 46.41 44.57 50 50 53.36 46.23 50.45 49.07 45.85 48.45 49.96 46.53 50.51 47.58 48.05 46.84 47.67 49.16 55.54 55.82 58.22 56.19 57.77 63.19 54.76 55.74 62.54 61.39 69.6 79.23 80 93.68 107.63 100.18 97.3 90.45 80.64 80.58 75.82 85.59 89.35 89.42 104.73 95.32 89.27 90.44 86.97 79.98 81.22 87.35 83.64 82.22 94.4 102.18
Data Y:
255 280.2 299.9 339.2 374.2 393.5 389.2 381.7 375.2 369 357.4 352.1 346.5 342.9 340.3 328.3 322.9 314.3 308.9 294 285.6 281.2 280.3 278.8 274.5 270.4 263.4 259.9 258 262.7 284.7 311.3 322.1 327 331.3 333.3 321.4 327 320 314.7 316.7 314.4 321.3 318.2 307.2 301.3 287.5 277.7 274.4 258.8 253.3 251 248.4 249.5 246.1 244.5 243.6 244 240.8 249.8 248 259.4 260.5 260.8 261.3 259.5 256.6 257.9 256.5 254.2 253.3 253.8 255.5 257.1 257.3 253.2 252.8 252 250.7 252.2 250 251 253.4 251.2 255.6 261.1 258.9 259.9 261.2 264.7 267.1 266.4 267.7 268.6 267.5 268.5 268.5 270.5 270.9 270.1 269.3 269.8 270.1 264.9 263.7 264.8 263.7 255.9 276.2 360.1 380.5 373.7 369.8 366.6 359.3 345.8 326.2 324.5 328.1 327.5 324.4 316.5 310.9 301.5 291.7 290.4 287.4 277.7 281.6 288 276 272.9 283 283.3 276.8 284.5 282.7 281.2 287.4 283.1 284 285.5 289.2 292.5 296.4 305.2 303.9 311.5 316.3 316.7 322.5 317.1 309.8 303.8 290.3 293.7 291.7 296.5 289.1 288.5 293.8 297.7 305.4 302.7 302.5 303 294.5 294.1 294.5 297.1 289.4 292.4 287.9 286.6 280.5 272.4 269.2 270.6 267.3 262.5 266.8 268.8 263.1 261.2 266 262.5 265.2 261.3 253.7 249.2 239.1 236.4 235.2 245.2 246.2 247.7 251.4 253.3 254.8 250 249.3 241.5 243.3 248 253 252.9 251.5 251.6 253.5 259.8 334.1 448 445.8 445 448.2 438.2 439.8 423.4 410.8 408.4 406.7 405.9 402.7 405.1 399.6 386.5 381.4 375.2 357.7 359 355 352.7 344.4 343.8 338 339 333.3 334.4 328.3 330.7 330 331.6 351.2 389.4 410.9 442.8 462.8 466.9 461.7 439.2 430.3 416.1 402.5 397.3 403.3 395.9 387.8 378.6 377.1 370.4 362 350.3 348.2 344.6 343.5 342.8 347.6 346.6 349.5 342.1 342 342.8 339.3 348.2 333.7 334.7 354 367.7 363.3 358.4 353.1 343.1 344.6 344.4 333.9 331.7 324.3 321.2 322.4 321.7 320.5 312.8 309.7 315.6 309.7 304.6 302.5 301.5 298.8 291.3 293.6 294.6 285.9 297.6 301.1 293.8 297.7 292.9 292.1 287.2 288.2 283.8 299.9 292.4 293.3 300.8 293.7 293.1 294.4 292.1 291.9 282.5 277.9 287.5 289.2 285.6 293.2 290.8 283.1 275 287.8 287.8 287.4 284 277.8 277.6 304.9 294 300.9 324 332.9 341.6 333.4 348.2 344.7 344.7 329.3 323.5 323.2 317.4 330.1 329.2 334.9 315.8 315.4 319.6 317.3 313.8 315.8 311.3
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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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