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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 14 Dec 2008 07:15:18 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/14/t1229264334z6olwwr6g3arx3u.htm/, Retrieved Wed, 15 May 2024 12:17:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33388, Retrieved Wed, 15 May 2024 12:17:02 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact156
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-14 14:15:18] [d300b7a0882cee7d84584ad37a3d4ede] [Current]
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Dataseries X:
101,02
100,67
100,47
100,38
100,33
100,34
100,37
100,39
100,21
100,21
100,22
100,28
100,25
100,25
100,21
100,16
100,18
100,1
99,96
99,88
99,88
99,86
99,84
99,8
99,82
99,81
99,92
100,03
99,99
100,02
100,01
100,13
100,33
100,13
99,96
100,05
99,83
99,8
100,01
100,1
100,13
100,16
100,41
101,34
101,65
101,85
102,07
102,12
102,14
102,21
102,28
102,19
102,33
102,54
102,44
102,78
102,9
103,08
102,77
102,65
102,71
103,29
102,86
103,45
103,72
103,65
103,83
104,45
105,14
105,07
105,31
105,19
105,3
105,02
105,17
105,28
105,45
105,38
105,8
105,96
105,08
105,11
105,61
105,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33388&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33388&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33388&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.40750.2316786567640620.810000000000002
2100.0308333333330.1761434504928170.450000000000003
3100.0166666666670.141378494785730.519999999999996
4100.7891666666670.9310840049331892.32000000000001
5102.5258333333330.3096173102200190.939999999999998
6104.0558333333330.941077316245332.60000000000001
7105.3883333333330.2918851995168120.939999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.4075 & 0.231678656764062 & 0.810000000000002 \tabularnewline
2 & 100.030833333333 & 0.176143450492817 & 0.450000000000003 \tabularnewline
3 & 100.016666666667 & 0.14137849478573 & 0.519999999999996 \tabularnewline
4 & 100.789166666667 & 0.931084004933189 & 2.32000000000001 \tabularnewline
5 & 102.525833333333 & 0.309617310220019 & 0.939999999999998 \tabularnewline
6 & 104.055833333333 & 0.94107731624533 & 2.60000000000001 \tabularnewline
7 & 105.388333333333 & 0.291885199516812 & 0.939999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33388&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]100.4075[/C][C]0.231678656764062[/C][C]0.810000000000002[/C][/ROW]
[ROW][C]2[/C][C]100.030833333333[/C][C]0.176143450492817[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]3[/C][C]100.016666666667[/C][C]0.14137849478573[/C][C]0.519999999999996[/C][/ROW]
[ROW][C]4[/C][C]100.789166666667[/C][C]0.931084004933189[/C][C]2.32000000000001[/C][/ROW]
[ROW][C]5[/C][C]102.525833333333[/C][C]0.309617310220019[/C][C]0.939999999999998[/C][/ROW]
[ROW][C]6[/C][C]104.055833333333[/C][C]0.94107731624533[/C][C]2.60000000000001[/C][/ROW]
[ROW][C]7[/C][C]105.388333333333[/C][C]0.291885199516812[/C][C]0.939999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33388&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33388&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
1100.40750.2316786567640620.810000000000002
2100.0308333333330.1761434504928170.450000000000003
3100.0166666666670.141378494785730.519999999999996
4100.7891666666670.9310840049331892.32000000000001
5102.5258333333330.3096173102200190.939999999999998
6104.0558333333330.941077316245332.60000000000001
7105.3883333333330.2918851995168120.939999999999998







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.35670111114123
beta0.0469981862076677
S.D.0.0696295075360184
T-STAT0.674975134404853
p-value0.529638379587051

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.35670111114123 \tabularnewline
beta & 0.0469981862076677 \tabularnewline
S.D. & 0.0696295075360184 \tabularnewline
T-STAT & 0.674975134404853 \tabularnewline
p-value & 0.529638379587051 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33388&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.35670111114123[/C][/ROW]
[ROW][C]beta[/C][C]0.0469981862076677[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0696295075360184[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.674975134404853[/C][/ROW]
[ROW][C]p-value[/C][C]0.529638379587051[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33388&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33388&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)
alpha-4.35670111114123
beta0.0469981862076677
S.D.0.0696295075360184
T-STAT0.674975134404853
p-value0.529638379587051







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-69.0052560165646
beta14.6866754264023
S.D.14.7326651062435
T-STAT0.996878386937494
p-value0.364591119701246
Lambda-13.6866754264023

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -69.0052560165646 \tabularnewline
beta & 14.6866754264023 \tabularnewline
S.D. & 14.7326651062435 \tabularnewline
T-STAT & 0.996878386937494 \tabularnewline
p-value & 0.364591119701246 \tabularnewline
Lambda & -13.6866754264023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33388&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-69.0052560165646[/C][/ROW]
[ROW][C]beta[/C][C]14.6866754264023[/C][/ROW]
[ROW][C]S.D.[/C][C]14.7326651062435[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.996878386937494[/C][/ROW]
[ROW][C]p-value[/C][C]0.364591119701246[/C][/ROW]
[ROW][C]Lambda[/C][C]-13.6866754264023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33388&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33388&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-69.0052560165646
beta14.6866754264023
S.D.14.7326651062435
T-STAT0.996878386937494
p-value0.364591119701246
Lambda-13.6866754264023



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')