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*The author of this computation has been verified* R Software Module: /rwasp_smp.wasp (opens new window with default values) Title produced by software: Standard Deviation-Mean Plot Date of computation: Sat, 19 Dec 2009 08:08:37 -0700   Cite this page as follows: Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/19/t1261235384csraxy7pyinf7gy.htm/, Retrieved Wed, 22 May 2013 05:13:47 +0000   Original text written by user:   IsPrivate? No (this computation is public)   User-defined keywords:   System-generated keywords (parent): (pk = 0) Estimated Impact 38   Dataseries X: » Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability « 110,3 103,9 101,6 94,6 95,9 104,7 102,8 98,1 119,9 80,9 95,7 113,2 105,9 108,8 102,3 99 100,7 115,5 100,7 109,9 114,6 85,4 100,5 114,8 116,5 112,9 102 106 105,3 118,8 106,1 109,3 117,2 92,5 104,2 112,2 122,4 113,1 100 110,7 112,8 109,8 117,3 109,1 115,9 96 99,8 116,8 115,7 99,4 94,3 91 93,2 103,1 94,1 91,8 102,7 82,6 89,1 104,5   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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Standard Deviation-Mean Plot Section Mean Standard Deviation Range 1 101.8 10.0816665289028 39 2 104.841666666667 8.64496262501341 30.1 3 108.583333333333 7.49773703233586 26.3 4 110.308333333333 8.01015926902527 26.4 5 96.7916666666667 8.75852398662254 33.1 Regression: S.E.(k) = alpha + beta * Mean(k) alpha 20.3027414826687 beta -0.112038784227145 S.D. 0.0811123257347942 T-STAT -1.38127939511275 p-value 0.261095267556751 Regression: ln S.E.(k) = alpha + beta * ln Mean(k) alpha 8.37658214571886 beta -1.34042419063867 S.D. 0.95037659543428 T-STAT -1.41041372133765 p-value 0.253223242416548 Lambda 2.34042419063867   Charts produced by software: http://www.freestatistics.org/blog/date/2009/Dec/19/t1261235384csraxy7pyinf7gy/1cho61261235315.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/19/t1261235384csraxy7pyinf7gy/1cho61261235315.ps (opens in new window) Click here to open pdf file. http://www.freestatistics.org/blog/date/2009/Dec/19/t1261235384csraxy7pyinf7gy/2b2jx1261235315.png (opens in new window) http://www.freestatistics.org/blog/date/2009/Dec/19/t1261235384csraxy7pyinf7gy/2b2jx1261235315.ps (opens in new window) Click here to open pdf file.   Parameters (Session): par1 = 12 ;   Parameters (R input): par1 = 12 ;   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')