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Type 'q()' to quit R. > x <- c(2.12,2.12,2.13,2.14,2.15,2.15,2.16,2.17,2.17,2.18,2.17,2.17,2.18,2.17,2.18,2.18,2.18,2.17,2.17,2.18,2.17,2.18,2.17,2.17,2.17,2.17,2.17,2.17,2.17,2.17,2.17,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.18,2.19,2.19,2.19,2.2,2.2,2.21,2.21,2.21,2.2,2.21,2.2,2.21,2.21,2.22,2.22,2.23,2.24,2.24,2.25,2.25,2.32,2.36,2.37,2.37,2.37,2.38,2.38,2.41,2.42,2.43,2.44,2.44,2.44,2.43,2.43,2.43,2.42,2.42,2.42,2.42,2.42) > 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] 85 > (np <- floor(n / par1)) [1] 7 > 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] [1,] 2.12 2.18 2.17 2.18 2.20 2.24 2.42 [2,] 2.12 2.17 2.17 2.18 2.21 2.24 2.43 [3,] 2.13 2.18 2.17 2.18 2.21 2.25 2.44 [4,] 2.14 2.18 2.17 2.18 2.21 2.25 2.44 [5,] 2.15 2.18 2.17 2.18 2.20 2.32 2.44 [6,] 2.15 2.17 2.17 2.18 2.21 2.36 2.43 [7,] 2.16 2.17 2.17 2.18 2.20 2.37 2.43 [8,] 2.17 2.18 2.18 2.18 2.21 2.37 2.43 [9,] 2.17 2.17 2.18 2.19 2.21 2.37 2.42 [10,] 2.18 2.18 2.18 2.19 2.22 2.38 2.42 [11,] 2.17 2.17 2.18 2.19 2.22 2.38 2.42 [12,] 2.17 2.17 2.18 2.20 2.23 2.41 2.42 > 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] 2.152500 2.175000 2.174167 2.184167 2.210833 2.328333 2.428333 > arr.sd [1] 0.020943647 0.005222330 0.005149287 0.006685579 0.009003366 0.064784023 [7] 0.008348471 > arr.range [1] 0.06 0.01 0.01 0.02 0.03 0.17 0.02 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean -0.1454 0.0727 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -9.843 6.623 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean -0.3585 0.1808 > postscript(file="/var/www/html/rcomp/tmp/1gt6o1262428492.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/221hp1262428492.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/3ci0s1262428492.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/4mi1b1262428492.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/5q5271262428492.tab") > > try(system("convert tmp/1gt6o1262428492.ps tmp/1gt6o1262428492.png",intern=TRUE)) character(0) > try(system("convert tmp/221hp1262428492.ps tmp/221hp1262428492.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.497 0.275 1.060