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Type 'q()' to quit R. > x <- c(7.5,7.2,7,6.9,7,6.9,6.9,6.9,6.8,7,6.8,6.8,6.7,6.4,6.2,6.1,6.2,6.5,6.6,6.5,6.2,6.2,6.6,7.1,7.3,7.4,7.4,7.4,7.4,7.3,7.3,7.4,7.6,7.6,7.6,7.6,7.8,7.9,8.1,8.2,8.2,8.1,8.1,8.1,8.1,8.1,8.2,8.3,8.4,8.5,8.6,8.5,8.3,7.8,7.8,8,8.6,8.9,8.9,8.3,8.3,8.3,8.4,8.5,8.4,8.6,8.5,8.5,8.4,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.6,8.4,8.1,8,8,8,8,7.9,7.8,7.8,7.9,8.1,8,7.6,7.3,7,6.8,7,7.1,7.2,7.1,6.9,6.7,6.7,6.6,6.9,7.3,7.4,7.3,7,6.9,7.1,7.5,7.7,7.9,7.8,7.7,7.8,7.8,7.9,8,8.1) > par1 = '12' > #'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] 119 > (np <- floor(n / par1)) [1] 9 > 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] [1,] 7.5 6.7 7.3 7.8 8.4 8.3 8.5 7.9 7.2 [2,] 7.2 6.4 7.4 7.9 8.5 8.3 8.5 7.8 7.1 [3,] 7.0 6.2 7.4 8.1 8.6 8.4 8.5 7.8 6.9 [4,] 6.9 6.1 7.4 8.2 8.5 8.5 8.5 7.9 6.7 [5,] 7.0 6.2 7.4 8.2 8.3 8.4 8.5 8.1 6.7 [6,] 6.9 6.5 7.3 8.1 7.8 8.6 8.6 8.0 6.6 [7,] 6.9 6.6 7.3 8.1 7.8 8.5 8.4 7.6 6.9 [8,] 6.9 6.5 7.4 8.1 8.0 8.5 8.1 7.3 7.3 [9,] 6.8 6.2 7.6 8.1 8.6 8.4 8.0 7.0 7.4 [10,] 7.0 6.2 7.6 8.1 8.9 8.5 8.0 6.8 7.3 [11,] 6.8 6.6 7.6 8.2 8.9 8.5 8.0 7.0 7.0 [12,] 6.8 7.1 7.6 8.3 8.3 8.5 8.0 7.1 6.9 > 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] 6.975000 6.441667 7.441667 8.100000 8.383333 8.450000 8.300000 7.525000 [9] 7.000000 > arr.sd [1] 0.2005674 0.2874918 0.1240112 0.1348400 0.3688639 0.0904534 0.2522625 [8] 0.4575130 0.2628515 > arr.range [1] 0.7 1.0 0.3 0.5 1.1 0.3 0.6 1.3 0.8 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 0.44687 -0.02686 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 1.421 -1.459 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 1.8114 -0.1414 > postscript(file="/var/www/html/rcomp/tmp/1668j1261224558.ps",horizontal=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/html/rcomp/tmp/2zxa91261224558.ps",horizontal=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/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/html/rcomp/tmp/3u32x1261224558.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/html/rcomp/tmp/4fxo41261224558.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/html/rcomp/tmp/5hqft1261224558.tab") > > try(system("convert tmp/1668j1261224558.ps tmp/1668j1261224558.png",intern=TRUE)) character(0) > try(system("convert tmp/2zxa91261224558.ps tmp/2zxa91261224558.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.513 0.300 1.246