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Data X:
78973 46146 46492 60656 21898 36555 74680 22807 61282 37981 41553 45081 38557 51641 30658 52924 79256 53462 68950 53639 67819 48333 28001 51665 39019 46221 65792 39858 19574 41829 78688 36781 44314 24874 56911 37048 48426 33388 26998 46502 41507 40001 33144 29501 43059 43249 29272 49821 98341 44372 42448 5950 64839 32551 30767 62046 71930 67328 67253 35373 85544 88087 30621 50580 49670 25456 69245 43787 53638 35683 38008 18801 44324 51408 53880 55708 63858 183643 35660 41664 29883 62047 33321 46553 56622 15430 49379 58215 38253 77786 21331 55292 30105 37651 59370 46216 73122 93927 55935 93308 74344 78094 25625 43750 28995 47336 57582 60875 165877 32984 61638 36367 1168 40530 21427 15024 39088 855 80455 14116 43915 76705 40112 41821 8773 52045 51491 53470 53211 63091 131634 41745 23656 51442 54574 35708 66627 39585 50029 25266 34860 62759 62307 37238 42452 59820 75075 97567 0 6023 0 0 0 0 42420 31116 0 0 1644 6179 3926 23238 0 38818
Data Y:
93809 75589 61071 64672 39014 32213 131696 6853 43253 57555 85473 44501 42453 67285 57056 94982 89324 60461 64491 60717 83022 91708 28378 59360 54436 70629 95409 68631 42319 91440 100462 41411 94894 16617 114686 64881 106679 54866 45988 82618 79199 46657 71070 29970 42948 61186 47824 62913 101444 61145 58388 15049 81451 25109 44688 77378 80180 96279 115202 31648 119420 121683 46568 57903 71075 63394 58118 62099 63739 35768 53318 22330 57871 52090 50767 68496 101760 58441 38972 43530 38996 98432 49867 56434 55792 25155 43461 65474 82234 49606 47992 63723 39066 54501 69924 58204 80248 106887 82830 125642 62525 93166 30028 19630 56584 63525 68879 80800 56474 25551 77587 60521 5841 54108 24587 23872 116211 6622 83478 13155 87473 43580 10439 33067 13983 52276 81079 63507 106262 92878 120184 63110 29996 55746 105611 6783 69866 39663 93382 42310 1472 83141 70434 10901 66220 25867 71760 94809 0 7953 0 0 0 0 63404 89657 0 0 4245 21509 7670 10641 0 31359
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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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