Deviation Mean Plot Kwartz Uurwerken Danielle Versmissen

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

Title produced by software: Standard Deviation-Mean Plot

Date of computation: Sun, 18 May 2008 10:49:00 -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/May/18/t12111293997iaxqxtlmnc3wpq.htm/, Retrieved Sun, 18 May 2008 18:50:00 +0200

User-defined keywords:

Dataseries X:

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120.05 120.05 120.08 120.12 120.18 120.2 120.25 120.25 120.24 120.29 120.25 120.26 120.32 120.31 120.36 120.4 120.4 120.39 120.44 120.5 120.53 120.64 120.78 120.94 121 121.05 121.15 121.07 121.18 121.46 121.71 121.71 121.74 121.76 121.76 121.82 121.82 121.82 121.94 121.99 122.18 122.41 122.48 122.52 122.62 122.63 122.74 122.58 122.59 122.61 122.63 122.37 122.36 122.47 122.46 122.45 122.49 122.5 122.37 122.37 122.51 122.51 122.55 122.56 122.72 122.97 123.03 123.05 123.08 123.08 123.12 123.07 123.04 123.06 123.39 124.02 124.05 123.99 124.46 124.46 124.6 124.84 124.84 124.99 125.02

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 120.075 0.0331662479035574 0.0700000000000074 2 120.22 0.0355902608401013 0.0699999999999932 3 120.26 0.0216024689946973 0.0500000000000114 4 120.3475 0.0411298755975134 0.0900000000000034 5 120.4325 0.0499165971062383 0.109999999999999 6 120.7225 0.177458915433027 0.409999999999997 7 121.0675 0.0623832242407123 0.150000000000006 8 121.515 0.252520626220243 0.529999999999987 9 121.77 0.0346410161513748 0.0799999999999983 10 121.8925 0.0861684396980719 0.170000000000002 11 122.3975 0.151959424408839 0.339999999999989 12 122.6425 0.0684957419601129 0.159999999999997 13 122.55 0.121106014163897 0.259999999999991 14 122.435 0.0506622805119015 0.109999999999999 15 122.4325 0.0722841614740008 0.129999999999995 16 122.5325 0.0262995563967631 0.0499999999999972 17 122.9425 0.152178623115513 0.329999999999998 18 123.0875 0.0221735578260879 0.0500000000000114 19 123.3775 0.457411193566572 0.97999999999999 20 124.24 0.255212329900678 0.469999999999999 21 124.8175 0.161322658049018 0.390000000000001 Regression: S.E.(k) = alpha + beta * Mean(k) alpha -4.43180761669198 beta 0.0372407002474241 S.D. 0.0161455465899099 T-STAT 2.30656175311510 p-value 0.0325122182677801 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha -193.311870630718 beta 39.70512684832 S.D. 15.8599836850787 T-STAT 2.5034784169214 p-value 0.0215815429889178 Lambda -38.7051268483200

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t12111293997iaxqxtlmnc3wpq/1w3ah1211129338.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t12111293997iaxqxtlmnc3wpq/1w3ah1211129338.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t12111293997iaxqxtlmnc3wpq/2ejly1211129338.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t12111293997iaxqxtlmnc3wpq/2ejly1211129338.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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