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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 24 Nov 2007 03:45:30 -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/2007/Nov/24/t11959006368o497uoj54assjv.htm/, Retrieved Fri, 03 May 2024 07:20:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6258, Retrieved Fri, 03 May 2024 07:20:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsG19Q1d
Estimated Impact238
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2007-11-24 10:45:30] [6b5c00822e2ce0f7cf73539c28d95782] [Current]
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Dataseries X:
107,97
108,13
108,54
109,86
109,75
109,99
112,01
111,96
111,41
112,11
111,67
111,95
112,31
113,26
113,5
114,43
115,02
115,1
117,11
117,52
116,1
116,39
116,01
116,74
116,68
117,45
117,8
119,37
118,9
119,05
120,46
120,99
119,86
120,18
119,81
120,15
119,8
120,27
120,71
121,87
121,87
121,92
123,72
124,38
123,21
123,17
122,95
123,46
123,24
123,86
124,28
124,78
125,19
125,46
127,6
127,8
126,63
127,06
126,77
127,05




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6258&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6258&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6258&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1110.4458333333331.605663036841414.14
2115.2908333333331.64665754199419.39
3119.2251.3131883476347312.45
4122.27751.4492325555272314.52
5125.811.5425598559183718.05

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 110.445833333333 & 1.60566303684141 & 4.14 \tabularnewline
2 & 115.290833333333 & 1.6466575419941 & 9.39 \tabularnewline
3 & 119.225 & 1.31318834763473 & 12.45 \tabularnewline
4 & 122.2775 & 1.44923255552723 & 14.52 \tabularnewline
5 & 125.81 & 1.54255985591837 & 18.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6258&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]110.445833333333[/C][C]1.60566303684141[/C][C]4.14[/C][/ROW]
[ROW][C]2[/C][C]115.290833333333[/C][C]1.6466575419941[/C][C]9.39[/C][/ROW]
[ROW][C]3[/C][C]119.225[/C][C]1.31318834763473[/C][C]12.45[/C][/ROW]
[ROW][C]4[/C][C]122.2775[/C][C]1.44923255552723[/C][C]14.52[/C][/ROW]
[ROW][C]5[/C][C]125.81[/C][C]1.54255985591837[/C][C]18.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6258&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6258&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
1110.4458333333331.605663036841414.14
2115.2908333333331.64665754199419.39
3119.2251.3131883476347312.45
4122.27751.4492325555272314.52
5125.811.5425598559183718.05







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2.62364599723438
beta-0.00937684252978925
S.D.0.0116836331445781
T-STAT-0.802562217912555
p-value0.480920995677809

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.62364599723438 \tabularnewline
beta & -0.00937684252978925 \tabularnewline
S.D. & 0.0116836331445781 \tabularnewline
T-STAT & -0.802562217912555 \tabularnewline
p-value & 0.480920995677809 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6258&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.62364599723438[/C][/ROW]
[ROW][C]beta[/C][C]-0.00937684252978925[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0116836331445781[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.802562217912555[/C][/ROW]
[ROW][C]p-value[/C][C]0.480920995677809[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6258&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6258&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)
alpha2.62364599723438
beta-0.00937684252978925
S.D.0.0116836331445781
T-STAT-0.802562217912555
p-value0.480920995677809







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.91329884165653
beta-0.733736674392737
S.D.0.940134596129875
T-STAT-0.780459178306183
p-value0.492040145578392
Lambda1.73373667439274

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.91329884165653 \tabularnewline
beta & -0.733736674392737 \tabularnewline
S.D. & 0.940134596129875 \tabularnewline
T-STAT & -0.780459178306183 \tabularnewline
p-value & 0.492040145578392 \tabularnewline
Lambda & 1.73373667439274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6258&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.91329884165653[/C][/ROW]
[ROW][C]beta[/C][C]-0.733736674392737[/C][/ROW]
[ROW][C]S.D.[/C][C]0.940134596129875[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.780459178306183[/C][/ROW]
[ROW][C]p-value[/C][C]0.492040145578392[/C][/ROW]
[ROW][C]Lambda[/C][C]1.73373667439274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6258&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6258&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)
alpha3.91329884165653
beta-0.733736674392737
S.D.0.940134596129875
T-STAT-0.780459178306183
p-value0.492040145578392
Lambda1.73373667439274



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')