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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 16 Dec 2008 10:05:34 -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/16/t12294471802cip1xl73h17av2.htm/, Retrieved Wed, 15 May 2024 06:14:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34036, Retrieved Wed, 15 May 2024 06:14:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact232
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2008-12-16 17:05:34] [a5ed2c45dea395ef181ba16fe56905d7] [Current]
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Dataseries X:
108.65
107.03
104.21
103.02
101.45
100.34
112.6
118.56
119.32
116.97
109.56
109.58
110.74
110.41
109.44
107.3
105.78
105.99
120.23
122.17
121.66
120.64
118.46
119.16
120.77
120.27
118.62
118.44
116.51
117.94
132.44
134.86
134.46
131.54
127.33
129.06
130.81
130.47
129.19
126.46
124.84
126.25
138.07
142.08
142.51
142.21
138.22
138.52
137.45
137.11
135.95
133.32
132.01
132.37
144.4
146.3
146.14
142.4
138.51
138.91
138.04
137.27
134.88
133.58
133.24
133.28
144.13
145.58
144.21
136.7
131.61
129.64
130.41
127.68
123.68
122.34
118.88
116
129.19
131.34
126
122.61
118.6
119.63




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34036&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34036&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1109.2741666666676.5284753313093818.98
2114.3316666666676.5674954868425316.39
3125.1866666666677.0855696291615818.35
4134.1358333333336.7842443919494117.67
5138.7391666666675.0881135249151314.2900000000000
6136.8466666666675.2638412060418615.9400000000000
7123.8633333333335.0675389998648815.34

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 109.274166666667 & 6.52847533130938 & 18.98 \tabularnewline
2 & 114.331666666667 & 6.56749548684253 & 16.39 \tabularnewline
3 & 125.186666666667 & 7.08556962916158 & 18.35 \tabularnewline
4 & 134.135833333333 & 6.78424439194941 & 17.67 \tabularnewline
5 & 138.739166666667 & 5.08811352491513 & 14.2900000000000 \tabularnewline
6 & 136.846666666667 & 5.26384120604186 & 15.9400000000000 \tabularnewline
7 & 123.863333333333 & 5.06753899986488 & 15.34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34036&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]109.274166666667[/C][C]6.52847533130938[/C][C]18.98[/C][/ROW]
[ROW][C]2[/C][C]114.331666666667[/C][C]6.56749548684253[/C][C]16.39[/C][/ROW]
[ROW][C]3[/C][C]125.186666666667[/C][C]7.08556962916158[/C][C]18.35[/C][/ROW]
[ROW][C]4[/C][C]134.135833333333[/C][C]6.78424439194941[/C][C]17.67[/C][/ROW]
[ROW][C]5[/C][C]138.739166666667[/C][C]5.08811352491513[/C][C]14.2900000000000[/C][/ROW]
[ROW][C]6[/C][C]136.846666666667[/C][C]5.26384120604186[/C][C]15.9400000000000[/C][/ROW]
[ROW][C]7[/C][C]123.863333333333[/C][C]5.06753899986488[/C][C]15.34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34036&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
1109.2741666666676.5284753313093818.98
2114.3316666666676.5674954868425316.39
3125.1866666666677.0855696291615818.35
4134.1358333333336.7842443919494117.67
5138.7391666666675.0881135249151314.2900000000000
6136.8466666666675.2638412060418615.9400000000000
7123.8633333333335.0675389998648815.34







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha10.5885037168162
beta-0.0359644794293014
S.D.0.0307366197957974
T-STAT-1.17008570455164
p-value0.294699015476608

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 10.5885037168162 \tabularnewline
beta & -0.0359644794293014 \tabularnewline
S.D. & 0.0307366197957974 \tabularnewline
T-STAT & -1.17008570455164 \tabularnewline
p-value & 0.294699015476608 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34036&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.5885037168162[/C][/ROW]
[ROW][C]beta[/C][C]-0.0359644794293014[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0307366197957974[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.17008570455164[/C][/ROW]
[ROW][C]p-value[/C][C]0.294699015476608[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34036&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34036&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)
alpha10.5885037168162
beta-0.0359644794293014
S.D.0.0307366197957974
T-STAT-1.17008570455164
p-value0.294699015476608







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha5.46405280663482
beta-0.759830365163475
S.D.0.63873997613629
T-STAT-1.18957696958261
p-value0.287616166548062
Lambda1.75983036516348

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.46405280663482 \tabularnewline
beta & -0.759830365163475 \tabularnewline
S.D. & 0.63873997613629 \tabularnewline
T-STAT & -1.18957696958261 \tabularnewline
p-value & 0.287616166548062 \tabularnewline
Lambda & 1.75983036516348 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34036&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.46405280663482[/C][/ROW]
[ROW][C]beta[/C][C]-0.759830365163475[/C][/ROW]
[ROW][C]S.D.[/C][C]0.63873997613629[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.18957696958261[/C][/ROW]
[ROW][C]p-value[/C][C]0.287616166548062[/C][/ROW]
[ROW][C]Lambda[/C][C]1.75983036516348[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34036&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34036&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)
alpha5.46405280663482
beta-0.759830365163475
S.D.0.63873997613629
T-STAT-1.18957696958261
p-value0.287616166548062
Lambda1.75983036516348



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')