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Type 'q()' to quit R. > x <- c(7.24,7.52,7.57,7.59,7.58,7.55,7.52,7.55,7.62,7.64,7.68,7.69,7.7,7.6,7.51,7.66,7.69,7.66,7.7,7.72,7.74,7.76,7.72,7.73,7.75,8.1,8.22,8.32,8.07,8.18,8.33,8.34,8.25,8.36,8.36,8.34,8.41,8.39,8.43,8.44,8.49,8.47,8.53,8.52,8.51,8.53,8.54,8.53,8.47,8.63,8.67,8.73,8.57,8.55,8.63,8.65,8.44,8.62,8.37,8.59,8.84,8.72,8.8,8.69,8.68,8.57,8.85,8.85,8.85,8.93,8.75,8.78,8.77,9.03,9.01,9.07,8.99,9.02,8.99,8.98,8.94,8.94,8.75,8.86) > 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] 84 > (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,] 7.24 7.70 7.75 8.41 8.47 8.84 8.77 [2,] 7.52 7.60 8.10 8.39 8.63 8.72 9.03 [3,] 7.57 7.51 8.22 8.43 8.67 8.80 9.01 [4,] 7.59 7.66 8.32 8.44 8.73 8.69 9.07 [5,] 7.58 7.69 8.07 8.49 8.57 8.68 8.99 [6,] 7.55 7.66 8.18 8.47 8.55 8.57 9.02 [7,] 7.52 7.70 8.33 8.53 8.63 8.85 8.99 [8,] 7.55 7.72 8.34 8.52 8.65 8.85 8.98 [9,] 7.62 7.74 8.25 8.51 8.44 8.85 8.94 [10,] 7.64 7.76 8.36 8.53 8.62 8.93 8.94 [11,] 7.68 7.72 8.36 8.54 8.37 8.75 8.75 [12,] 7.69 7.73 8.34 8.53 8.59 8.78 8.86 > 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] 7.562500 7.682500 8.218333 8.482500 8.576667 8.775833 8.945833 > arr.sd [1] 0.11616016 0.06916712 0.17846993 0.05293650 0.10395220 0.09894519 0.10175356 > arr.range [1] 0.45 0.25 0.61 0.15 0.36 0.36 0.32 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 0.135662 -0.003919 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -2.0936 -0.1142 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 0.76575 -0.04911 > postscript(file="/var/yougetitorg/rcomp/tmp/11j7y1304513908.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/yougetitorg/rcomp/tmp/23jqn1304513908.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/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/yougetitorg/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/yougetitorg/rcomp/tmp/39pvs1304513908.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/yougetitorg/rcomp/tmp/4naty1304513908.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/yougetitorg/rcomp/tmp/5zm681304513908.tab") > > try(system("convert tmp/11j7y1304513908.ps tmp/11j7y1304513908.png",intern=TRUE)) character(0) > try(system("convert tmp/23jqn1304513908.ps tmp/23jqn1304513908.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.550 0.340 0.809