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Type 'q()' to quit R. > x <- c(1200,1400,1210,1260,1320,1320,1310,1260,1340,1180,1330,1390,1130,1340,1140,1290,1260,1280,1330,1270,1300,1150,1410,1250,1030,1320,1160,1300,1190,1310,1290,1320,1300,1230,1330,1220,1010,1290,1170,1240,1260,1260,1310,1360,1250,1170,1360,1140,1030,1260,1210,1190,1230,1350,1300,1340,1270,1220,1400,1120,1000,1260,1260,1150,1240,1360,1350,1280,1320,1210,1370,1060,1040,1260,1210,1200,1200,1290,1400,1280,1280,1220,1350,1000,980,1240,1190,1200,1150,1270,1410,1420,1260,1300,1410,1000,950,1280,1330,1190,1170,1270,1340,1470,1270,1280,1430,980) > 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] 108 > (np <- floor(n / par1)) [1] 27 > 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] [,14] [1,] 1200 1320 1340 1130 1260 1300 1030 1190 1300 1010 1260 1250 1030 1230 [2,] 1400 1320 1180 1340 1280 1150 1320 1310 1230 1290 1260 1170 1260 1350 [3,] 1210 1310 1330 1140 1330 1410 1160 1290 1330 1170 1310 1360 1210 1300 [4,] 1260 1260 1390 1290 1270 1250 1300 1320 1220 1240 1360 1140 1190 1340 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [1,] 1270 1000 1240 1320 1040 1200 1280 980 1150 1260 950 1170 [2,] 1220 1260 1360 1210 1260 1290 1220 1240 1270 1300 1280 1270 [3,] 1400 1260 1350 1370 1210 1400 1350 1190 1410 1410 1330 1340 [4,] 1120 1150 1280 1060 1200 1280 1000 1200 1420 1000 1190 1470 [,27] [1,] 1270 [2,] 1280 [3,] 1430 [4,] 980 > 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] 1267.5 1302.5 1310.0 1225.0 1285.0 1277.5 1202.5 1277.5 1270.0 1177.5 [11] 1297.5 1230.0 1172.5 1305.0 1252.5 1167.5 1307.5 1240.0 1177.5 1292.5 [21] 1212.5 1152.5 1312.5 1242.5 1187.5 1312.5 1240.0 > arr.sd [1] 92.15024 28.72281 90.55385 105.98742 31.09126 108.12801 135.24669 [8] 59.65177 53.54126 122.03142 47.87136 98.31921 99.45686 54.46712 [15] 116.44026 123.11918 57.37305 137.35599 95.35023 82.20908 151.29992 [22] 117.01140 128.16006 173.66155 168.59715 126.06215 188.14888 > arr.range [1] 200 60 210 210 70 260 290 130 110 280 100 220 230 120 280 260 120 310 220 [20] 200 350 260 270 410 380 300 450 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean 602.7759 -0.4001 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) 47.422 -6.016 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 1343.4467 -0.8895 > postscript(file="/var/wessaorg/rcomp/tmp/1ixp31312374154.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/wessaorg/rcomp/tmp/2dwpa1312374154.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3k0321312374154.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/wessaorg/rcomp/tmp/4j73o1312374154.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/wessaorg/rcomp/tmp/5ew371312374154.tab") > > try(system("convert tmp/1ixp31312374154.ps tmp/1ixp31312374154.png",intern=TRUE)) character(0) > try(system("convert tmp/2dwpa1312374154.ps tmp/2dwpa1312374154.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.667 0.126 0.784