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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 23 Apr 2012 10:26:08 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/23/t1335191208pxgp0z9sumegfjm.htm/, Retrieved Fri, 03 May 2024 21:12:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164710, Retrieved Fri, 03 May 2024 21:12:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Spreidings- en ge...] [2012-04-23 14:26:08] [54d49d8a22bca19e9398641fe7fc5cc7] [Current]
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Dataseries X:
399.25
400.66
400.84
401.26
401.31
401.57
401.63
401.84
401.97
402
402
402
402.06
402.11
402.24
402.24
402.27
402.27
402.43
402.55
402.76
402.91
403.04
403.04
403.29
403.29
403.33
403.44
403.74
403.79
404.18
404.18
404.18
404.2
404.3
404.3
404.3
404.69
404.7
404.74
404.82
406.03
406.11
406.39
406.46
406.55
406.55
406.76
406.76
406.76
406.82
406.82
407.25
407.34
407.67
407.77
407.77
407.77
407.88
408.06




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164710&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164710&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164710&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1401.3608333333330.8075378778994982.75
2402.4933333333330.358337913994690.980000000000018
3403.8516666666670.4194765858312061.00999999999999
4405.6750.932635561679422.45999999999998
5407.3891666666670.4923313432183171.30000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 401.360833333333 & 0.807537877899498 & 2.75 \tabularnewline
2 & 402.493333333333 & 0.35833791399469 & 0.980000000000018 \tabularnewline
3 & 403.851666666667 & 0.419476585831206 & 1.00999999999999 \tabularnewline
4 & 405.675 & 0.93263556167942 & 2.45999999999998 \tabularnewline
5 & 407.389166666667 & 0.492331343218317 & 1.30000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164710&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]401.360833333333[/C][C]0.807537877899498[/C][C]2.75[/C][/ROW]
[ROW][C]2[/C][C]402.493333333333[/C][C]0.35833791399469[/C][C]0.980000000000018[/C][/ROW]
[ROW][C]3[/C][C]403.851666666667[/C][C]0.419476585831206[/C][C]1.00999999999999[/C][/ROW]
[ROW][C]4[/C][C]405.675[/C][C]0.93263556167942[/C][C]2.45999999999998[/C][/ROW]
[ROW][C]5[/C][C]407.389166666667[/C][C]0.492331343218317[/C][C]1.30000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164710&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164710&T=1

As an alternative you can also use a QR Code:  

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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1401.3608333333330.8075378778994982.75
2402.4933333333330.358337913994690.980000000000018
3403.8516666666670.4194765858312061.00999999999999
4405.6750.932635561679422.45999999999998
5407.3891666666670.4923313432183171.30000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0186521162652973
beta0.00144353820637512
S.D.0.0603755897139751
T-STAT0.0239093019747512
p-value0.982426380290615

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0186521162652973 \tabularnewline
beta & 0.00144353820637512 \tabularnewline
S.D. & 0.0603755897139751 \tabularnewline
T-STAT & 0.0239093019747512 \tabularnewline
p-value & 0.982426380290615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164710&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0186521162652973[/C][/ROW]
[ROW][C]beta[/C][C]0.00144353820637512[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0603755897139751[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0239093019747512[/C][/ROW]
[ROW][C]p-value[/C][C]0.982426380290615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164710&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164710&T=2

As an alternative you can also use a QR Code:  

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0186521162652973
beta0.00144353820637512
S.D.0.0603755897139751
T-STAT0.0239093019747512
p-value0.982426380290615







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-17.5534460955604
beta2.82849658559802
S.D.40.134059347682
T-STAT0.0704762147555201
p-value0.948249666119109
Lambda-1.82849658559802

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -17.5534460955604 \tabularnewline
beta & 2.82849658559802 \tabularnewline
S.D. & 40.134059347682 \tabularnewline
T-STAT & 0.0704762147555201 \tabularnewline
p-value & 0.948249666119109 \tabularnewline
Lambda & -1.82849658559802 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164710&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-17.5534460955604[/C][/ROW]
[ROW][C]beta[/C][C]2.82849658559802[/C][/ROW]
[ROW][C]S.D.[/C][C]40.134059347682[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0704762147555201[/C][/ROW]
[ROW][C]p-value[/C][C]0.948249666119109[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.82849658559802[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164710&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164710&T=3

As an alternative you can also use a QR Code:  

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-17.5534460955604
beta2.82849658559802
S.D.40.134059347682
T-STAT0.0704762147555201
p-value0.948249666119109
Lambda-1.82849658559802



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')