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Type 'q()' to quit R. > x <- c(31.5,31.29,31.3,31.06,31.09,31.11,31.13,31.1,31.03,30.74,30.83,30.82,30.8,30.74,30.71,30.58,30.71,30.7,30.7,30.72,30.68,30.78,30.84,30.8,30.8,30.88,30.87,30.92,30.82,30.75,30.75,30.75,30.63,30.52,30.58,30.6,30.6,30.63,30.56,30.61,30.53,30.6,30.6,30.63,30.66,30.34,30.32,30.3,30.3,30.08,29.96,29.91,29.83,29.89,29.85,30.06,29.83,29.95,30.02,30.03) > par1 = '4' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > (n <- length(x)) [1] 60 > (np <- floor(n / par1)) [1] 15 > arr <- array(NA,dim=c(par1,np)) > j <- 0 > k <- 1 > for (i in 1:(np*par1)) + { + j = j + 1 + arr[j,k] <- x[i] + if (j == par1) { + j = 0 + k=k+1 + } + } > arr [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 31.50 31.09 31.03 30.80 30.71 30.68 30.80 30.82 30.63 30.60 30.53 30.66 [2,] 31.29 31.11 30.74 30.74 30.70 30.78 30.88 30.75 30.52 30.63 30.60 30.34 [3,] 31.30 31.13 30.83 30.71 30.70 30.84 30.87 30.75 30.58 30.56 30.60 30.32 [4,] 31.06 31.10 30.82 30.58 30.72 30.80 30.92 30.75 30.60 30.61 30.63 30.30 [,13] [,14] [,15] [1,] 30.30 29.83 29.83 [2,] 30.08 29.89 29.95 [3,] 29.96 29.85 30.02 [4,] 29.91 30.06 30.03 > arr.mean <- array(NA,dim=np) > arr.sd <- array(NA,dim=np) > arr.range <- array(NA,dim=np) > for (j in 1:np) + { + arr.mean[j] <- mean(arr[,j],na.rm=TRUE) + arr.sd[j] <- sd(arr[,j],na.rm=TRUE) + arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) + } > arr.mean [1] 31.2875 31.1075 30.8550 30.7075 30.7075 30.7750 30.8675 30.7675 30.5825 [10] 30.6000 30.5900 30.4050 30.0625 29.9075 29.9575 > arr.sd [1] 0.179884222 0.017078251 0.123423391 0.092870878 0.009574271 0.068068593 [7] 0.049916597 0.035000000 0.046457866 0.029439203 0.042426407 0.170782513 [13] 0.173661548 0.104682058 0.092150240 > arr.range [1] 0.44 0.04 0.29 0.22 0.02 0.16 0.12 0.07 0.11 0.07 0.10 0.36 0.39 0.23 0.20 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 1.0498 -0.0316 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 65.27 -19.89 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 1.74239 -0.05078 > postscript(file="/var/www/rcomp/tmp/1fcle1323272730.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/2e6x31323272730.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') > dev.off() null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Section',header=TRUE) > a<-table.element(a,'Mean',header=TRUE) > a<-table.element(a,'Standard Deviation',header=TRUE) > a<-table.element(a,'Range',header=TRUE) > a<-table.row.end(a) > for (j in 1:np) { + a<-table.row.start(a) + a<-table.element(a,j,header=TRUE) + a<-table.element(a,arr.mean[j]) + a<-table.element(a,arr.sd[j] ) + a<-table.element(a,arr.range[j] ) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/3rdx01323272730.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'alpha',header=TRUE) > a<-table.element(a,lm1$coefficients[[1]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'beta',header=TRUE) > a<-table.element(a,lm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'T-STAT',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'p-value',header=TRUE) > a<-table.element(a,summary(lm1)$coefficients[2,4]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/40jwm1323272730.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'alpha',header=TRUE) > a<-table.element(a,lnlm1$coefficients[[1]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'beta',header=TRUE) > a<-table.element(a,lnlm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'T-STAT',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'p-value',header=TRUE) > a<-table.element(a,summary(lnlm1)$coefficients[2,4]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Lambda',header=TRUE) > a<-table.element(a,1-lnlm1$coefficients[[2]]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/54i151323272730.tab") > > try(system("convert tmp/1fcle1323272730.ps tmp/1fcle1323272730.png",intern=TRUE)) character(0) > try(system("convert tmp/2e6x31323272730.ps tmp/2e6x31323272730.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.968 0.220 1.593