Tutorial Hypothese 3 | ||||||||||||||||||||||||||||||
| *The author of this computation has been verified* | ||||||||||||||||||||||||||||||
| R Software Module: /rwasp_linear_regression.wasp (opens new window with default values) | ||||||||||||||||||||||||||||||
| Title produced by software: Linear Regression Graphical Model Validation | ||||||||||||||||||||||||||||||
| Date of computation: Sun, 07 Nov 2010 10:07:07 +0000 | ||||||||||||||||||||||||||||||
| Cite this page as follows: | ||||||||||||||||||||||||||||||
| Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Nov/07/t12891243352di38qkyonmn2bf.htm/, Retrieved Sun, 07 Nov 2010 11:05:35 +0100 | ||||||||||||||||||||||||||||||
| BibTeX entries for LaTeX users: | ||||||||||||||||||||||||||||||
@Manual{KEY,
author = {{YOUR NAME}},
publisher = {Office for Research Development and Education},
title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Nov/07/t12891243352di38qkyonmn2bf.htm/},
year = {2010},
}
@Manual{R,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Development Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2010},
note = {{ISBN} 3-900051-07-0},
url = {http://www.R-project.org},
}
| ||||||||||||||||||||||||||||||
| Original text written by user: | ||||||||||||||||||||||||||||||
| IsPrivate? | ||||||||||||||||||||||||||||||
| No (this computation is public) | ||||||||||||||||||||||||||||||
| User-defined keywords: | ||||||||||||||||||||||||||||||
| Dataseries X: | ||||||||||||||||||||||||||||||
| » Textbox « » Textfile « » CSV « | ||||||||||||||||||||||||||||||
| 85 105 108 92 112,5 112 104 69 94,5 68,5 104 103,5 123,5 93 50,5 89 107 78,5 115 114 85 81 83,5 112 101 103,5 93,5 112 140 83,5 90 84 110,5 96 95 121 99,5 142,5 118 104,5 102,5 89,5 95 98,5 94 108 63,5 84,5 93,5 112 148,5 112 109 91,5 75 84 107 92,5 109,5 84 102,5 106 77 111,5 114 75 73,5 93,5 105 113,5 140 77 84,5 113,5 77,5 117,5 98 112 101 95 81 91 142 98,5 112 116,5 98,5 83,5 133 91,5 72,5 106,5 67 122,5 74 144,5 84 72,5 64 116 84 93,5 111,5 92 115 85 108 108 85 86 110,5 98 105 76,5 84 128 87 128 111 79 90 84 112 93 117 84 99,5 95 84 134 171,5 98,5 118,5 94,5 105 104 83 105,5 84 86 81 94 78,5 119,5 133 119 95 112 75 92 112 98,5 112,5 112,5 108 108 88 106 92 117,5 84 112 100 112 84 127,5 80,5 93,5 86,5 92,5 108,5 121 112 114 84 81 111,5 81 70 140 117 84 112 150,5 147 105 119,5 84 91 101 117,5 121 133 112 91,5 105 etc... | ||||||||||||||||||||||||||||||
| Dataseries Y: | ||||||||||||||||||||||||||||||
| » Textbox « » Textfile « » CSV « | ||||||||||||||||||||||||||||||
| 56,3 62,3 63,3 59 62,5 62,5 59 56,5 62 53,8 61,5 61,5 64,5 58,3 51,3 58,8 65,3 59,5 61,3 63,3 61,8 53,5 58 61,3 63,3 61,5 60,8 59 65,5 56,3 64,3 58 64,3 57,5 57,8 61,5 62,3 61,8 65,3 58,3 62,8 59,3 61,5 62 61,3 62,3 52,8 59,8 59,5 61,3 63,5 64,8 60 59 55,8 57,8 61,3 62,3 64,3 55,5 64,5 60 56,3 58,3 60 54,5 55,8 62,8 60,5 63,3 66,8 60 60,5 64,3 58,3 66,5 65,3 60,5 59,5 59 61,3 61,5 64,8 56,8 66,5 61,5 63 57 65,5 62 56 61,3 55,5 61 54,5 66 56,5 56 51,5 62 63 61 64 61 59,8 61,3 63,3 63,5 61,5 60,3 61,3 64,8 60,5 57,3 59,5 60,8 60,5 67 64,8 50,5 57,5 60,5 61,8 61,3 66,3 53,3 59 57,8 60 68,3 67,5 63,8 65 59,5 66 61,8 57,3 66 56,5 58,3 61 62,8 59,3 67,3 66,3 64,5 60,5 66 57,5 64 68 63,5 69 63,8 66 63,5 59,5 66,3 57 60 57 67,3 62 65 59,5 67,8 58 60 58,5 58,3 61,5 65 66,5 68,5 57 61,5 66,5 52,5 55 71 66,5 58,8 66,3 65,8 71 59,5 69,8 etc... | ||||||||||||||||||||||||||||||
| Output produced by software: | ||||||||||||||||||||||||||||||
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| Charts produced by software: | ||||||||||||||||||||||||||||||
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| Parameters (Session): | ||||||||||||||||||||||||||||||
| par1 = 0 ; | ||||||||||||||||||||||||||||||
| Parameters (R input): | ||||||||||||||||||||||||||||||
| par1 = 0 ; | ||||||||||||||||||||||||||||||
| R code (references can be found in the software module): | ||||||||||||||||||||||||||||||
| 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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