## Free Statistics

of Irreproducible Research!

Author's title
Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 30 Apr 2020 22:14:17 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Apr/30/t1588277667ld2qi6crpfn2nmn.htm/, Retrieved Sun, 09 May 2021 02:28:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319143, Retrieved Sun, 09 May 2021 02:28:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact42
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2020-04-30 20:14:17] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
61,60,64,71,78,51,61,80,35,46,38,60,93,64,73,57,86

 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 Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319143&T=0

[TABLE]
[ROW]
 Summary of computational transaction[/C][/ROW] [ROW] Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW] Raw Output[/C] view raw output of R engine [/C][/ROW] [ROW] Computing time[/C] 1 seconds[/C][/ROW] [ROW] R Server[/C] Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=319143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319143&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 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 Big Analytics Cloud Computing Center

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 <- 0k <- 1for (i in 1:(np*par1)){j = j + 1arr[j,k] <- x[i]if (j == par1) {j = 0k=k+1}}arrarr.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.meanarr.sdarr.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')