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Type 'q()' to quit R. > x <- c(589,561,640,656,727,697,640,599,568,577,553,582,600,566,653,673,742,716,660,617,583,587,565,598,628,618,688,705,770,736,678,639,604,611,594,634,658,622,709,722,782,756,702,653,615,621,602,635,677,635,736,755,811,798,735,697,661,667,645,688,713,667,762,784,837,817,767,722,681,687,660,698,717,696,775,796,858,826,783,740,701,706,677,711,734,690,785,805,871,845,801,764,725,723,690,734,750,707,807,824,886,859,819,783,740,747,711,751,804,756,860,878,942,913,869,834,790,800,763,800,826,799,890,900,961,935,894,855,809,810,766,805,821,773,883,898,957,924,881,837,784,791,760,802,828,778,889,902,969,947,908,867,815,812,773,813,834,782,892,903,966,937,896,858,817,827,797,843) > 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] 168 > (np <- floor(n / par1)) [1] 14 > 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] [,13] [1,] 589 600 628 658 677 713 717 734 750 804 826 821 828 [2,] 561 566 618 622 635 667 696 690 707 756 799 773 778 [3,] 640 653 688 709 736 762 775 785 807 860 890 883 889 [4,] 656 673 705 722 755 784 796 805 824 878 900 898 902 [5,] 727 742 770 782 811 837 858 871 886 942 961 957 969 [6,] 697 716 736 756 798 817 826 845 859 913 935 924 947 [7,] 640 660 678 702 735 767 783 801 819 869 894 881 908 [8,] 599 617 639 653 697 722 740 764 783 834 855 837 867 [9,] 568 583 604 615 661 681 701 725 740 790 809 784 815 [10,] 577 587 611 621 667 687 706 723 747 800 810 791 812 [11,] 553 565 594 602 645 660 677 690 711 763 766 760 773 [12,] 582 598 634 635 688 698 711 734 751 800 805 802 813 [,14] [1,] 834 [2,] 782 [3,] 892 [4,] 903 [5,] 966 [6,] 937 [7,] 896 [8,] 858 [9,] 817 [10,] 827 [11,] 797 [12,] 843 > 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] 615.7500 630.0000 658.7500 673.0833 708.7500 732.9167 748.8333 763.9167 [9] 782.0000 834.0833 854.1667 842.5833 858.4167 862.6667 > arr.sd [1] 56.10562 58.53515 56.23672 59.61003 58.07069 59.33029 57.63969 58.35231 [9] 57.32206 58.78692 61.00497 64.52548 64.83049 56.57551 > arr.range [1] 174 177 176 180 176 177 181 181 179 186 195 197 196 184 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 46.46424 0.01670 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 2.7394 0.2022 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 127.44402 0.07333 > postscript(file="/var/www/html/rcomp/tmp/1kg5g1275220798.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/2kg5g1275220798.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/3nzmm1275220798.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/4rhka1275220798.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/5n9011275220798.tab") > > try(system("convert tmp/1kg5g1275220798.ps tmp/1kg5g1275220798.png",intern=TRUE)) character(0) > try(system("convert tmp/2kg5g1275220798.ps tmp/2kg5g1275220798.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.574 0.323 1.742