R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(1747,1245,1182,958,1000,1044,875,939,736,905,796,372,1326,668,962,912,1119,891,931,1047,982,1098,714,128,1784,828,1199,1095,977,1338,975,840,1324,1236,883,177,2186,809,1434,1365,1247,1476,1211,990,1205,1238,952,204,2135,1157,1290,1071,1169,1431,945,1034,1100,1297,921,236,1990,966,1326,908,1206,1861,929,1296,1332,1352,1040,148,2090,1435,1124,1319,1436,1774,1566,1385,1147,1274,625,52,1990,1154,954,887,825,966,954,770,1838,1371,589,116,1898,712,1175,1240,1329,1550,1201,938,1030,1060,1035,635,2565,910,1304,1331,1681,1983,1021,1061,1292,1274,1024,568,2570,1125,1600,1492,2492,3523,990,869,1310,979,1244,442,2956,1055,2004,1462,1144,1454,1538,1388,1547,1570,1535,1352,1888,999,1158,1342,1443,1519,1267,1454,987,1430,1254,734)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 156
> (np <- floor(n / par1))
[1] 13
> 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,] 1747 1326 1784 2186 2135 1990 2090 1990 1898  2565  2570  2956  1888
 [2,] 1245  668  828  809 1157  966 1435 1154  712   910  1125  1055   999
 [3,] 1182  962 1199 1434 1290 1326 1124  954 1175  1304  1600  2004  1158
 [4,]  958  912 1095 1365 1071  908 1319  887 1240  1331  1492  1462  1342
 [5,] 1000 1119  977 1247 1169 1206 1436  825 1329  1681  2492  1144  1443
 [6,] 1044  891 1338 1476 1431 1861 1774  966 1550  1983  3523  1454  1519
 [7,]  875  931  975 1211  945  929 1566  954 1201  1021   990  1538  1267
 [8,]  939 1047  840  990 1034 1296 1385  770  938  1061   869  1388  1454
 [9,]  736  982 1324 1205 1100 1332 1147 1838 1030  1292  1310  1547   987
[10,]  905 1098 1236 1238 1297 1352 1274 1371 1060  1274   979  1570  1430
[11,]  796  714  883  952  921 1040  625  589 1035  1024  1244  1535  1254
[12,]  372  128  177  204  236  148   52  116  635   568   442  1352   734
> 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]  983.2500  898.1667 1054.6667 1193.0833 1148.8333 1196.1667 1268.9167
 [8] 1034.5000 1150.2500 1334.5000 1553.0000 1583.7500 1289.5833
> arr.sd
 [1] 328.2956 299.4491 387.2623 465.5475 430.9448 474.0796 524.0086 511.8129
 [9] 343.8562 530.7260 878.4892 491.9655 299.6251
> arr.range
 [1] 1375 1198 1607 1982 1899 1842 2038 1874 1263 1997 3081 1901 1154
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
  -141.7413       0.4977  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.235          1.175  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
   -137.896        1.594  

> postscript(file="/var/wessaorg/rcomp/tmp/11nwg1448230617.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/2s2p61448230617.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/387jn1448230617.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4vx051448230617.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5nth31448230617.tab") 
> 
> try(system("convert tmp/11nwg1448230617.ps tmp/11nwg1448230617.png",intern=TRUE))
character(0)
> try(system("convert tmp/2s2p61448230617.ps tmp/2s2p61448230617.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.822   0.192   1.016