Raf Mattheussen SD mean plot roze garnalen

R Software Module: rwasp_smp.wasp (opens new window with default values)

Title produced by software: Standard Deviation-Mean Plot

Date of computation: Wed, 13 Aug 2008 07:01:29 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Aug/13/t1218632544hzso5hzmg2ycqyj.htm/, Retrieved Wed, 13 Aug 2008 13:02:24 +0000

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

16,8 16,91 16,91 17,16 17,02 17,23 17,22 17,29 17,3 17,22 17,19 17,23 17,36 17,39 17,29 17,28 17,4 17,51 17,54 17,64 17,65 17,5 17,37 17,56 17,49 17,61 17,79 17,83 17,56 17,95 18,09 18,38 18,38 18,44 18,84 19,01 19,06 19,06 18,97 18,98 19,41 19,55 19,64 19,71 19,48 19,48 19,41 19,25 19,14 19,21 19,3 19,53 19,14 19,16 19,24 19,38 19,27 19,27 19,07 19,15 19,24 19,36 19,57 19,59 19,36 19,46 19,65 19,46 19,51 19,64 19,64 19,69 19,28 19,67 19,65 19,6 19,53 19,64 19,67 19,81 19,73 19,87 19,97 20,12 19,94 20,31 20,13 20,22 20,38 20,44 20,34 20,14 19,97 19,82 19,98 20,12

Text written by user:

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 16.945 0.152424844868982 0.359999999999999 2 17.19 0.117473401244707 0.270000000000000 3 17.235 0.0465474668125632 0.109999999999999 4 17.33 0.0535412613473633 0.109999999999999 5 17.5225 0.0987842767515837 0.240000000000002 6 17.52 0.117473401244706 0.279999999999998 7 17.68 0.158745078663875 0.34 8 17.995 0.340832314586905 0.82 9 18.6675 0.306308667849933 0.630000000000003 10 19.0175 0.04924428900898 0.0899999999999999 11 19.5775 0.129453981527543 0.300000000000001 12 19.405 0.10847426730182 0.230000000000000 13 19.295 0.169803808359334 0.390000000000001 14 19.23 0.108934230922454 0.239999999999998 15 19.19 0.097979589711327 0.199999999999999 16 19.44 0.169115345252878 0.350000000000001 17 19.4825 0.121209185570511 0.289999999999999 18 19.62 0.0770281333886087 0.180000000000000 19 19.55 0.182391520270726 0.390000000000001 20 19.6625 0.115289490703474 0.279999999999998 21 19.9225 0.164392822227736 0.390000000000001 22 20.15 0.158113883008418 0.369999999999997 23 20.325 0.13 0.300000000000001 24 19.9725 0.122576506721313 0.300000000000001 Regression: S.E.(k) = alpha + beta * Mean(k) alpha 0.0788014550348941 beta 0.00310870796372912 S.D. 0.0135247694214224 T-STAT 0.229852936258204 p-value 0.820329725318831 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha -6.39897703186516 beta 1.46721920575673 S.D. 1.72592614172999 T-STAT 0.85010544210545 p-value 0.404423610150312 Lambda -0.467219205756727

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/13/t1218632544hzso5hzmg2ycqyj/1krd41218632481.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/13/t1218632544hzso5hzmg2ycqyj/1krd41218632481.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/13/t1218632544hzso5hzmg2ycqyj/2ryzk1218632481.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/13/t1218632544hzso5hzmg2ycqyj/2ryzk1218632481.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) 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 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 arr.sd arr.range (lm1 <- lm(arr.sd~arr.mean)) (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) (lm2 <- lm(arr.range~arr.mean)) bitmap(file='test1.png') plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') dev.off() bitmap(file='test2.png') plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') dev.off() load(file='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='mytable.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)$coefficients[2,4]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lnlm1$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='mytable2.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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