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Description of Statistical Computation

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 computationTue, 02 Dec 2008 12:40:41 -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/02/t1228246902qdqale2xog5tx5h.htm/, Retrieved Fri, 17 May 2024 02:02:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28265, Retrieved Fri, 17 May 2024 02:02:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [nsts Q8] [2008-12-02 19:40:41] [821c4b3d195be8e737cf8c9dc649d3cf] [Current]
F RMPD    [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 19:45:13] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F   P       [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 19:48:42] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMPD      [Standard Deviation-Mean Plot] [nsts Q8] [2008-12-02 19:54:11] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMPD        [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 19:58:11] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F   P           [(Partial) Autocorrelation Function] [nsts Q8] [2008-12-02 20:02:32] [3a9fc6d5b5e0e816787b7dbace57e7cd]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109,57
107,08
110,33
110,36
106,5
104,3
107,21
109,34
108,2
109,86
108,68
113,38
117,12
116,23
114,75
115,81
115,86
117,8
117,11
116,31
118,38
121,57
121,65
124,2
126,12
128,6
128,16
130,12
135,83
138,05
134,99
132,38
128,94
128,12
127,84
132,43
134,13
134,78
133,13
129,08
134,48
132,86
134,08
134,54
134,51
135,97
136,09
139,14
135,63
136,55
138,83
138,84
135,37
132,22
134,75
135,98
136,06
138,05
139,59
140,58

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28265&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28265&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28265&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1108.7341666666672.3180691743289.08
2118.0658333333332.894092598673549.45
3130.9653.7395199011248911.93
4134.3991666666672.3439145901804110.0600000000000
5136.8708333333332.368975453011228.36000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 108.734166666667 & 2.318069174328 & 9.08 \tabularnewline
2 & 118.065833333333 & 2.89409259867354 & 9.45 \tabularnewline
3 & 130.965 & 3.73951990112489 & 11.93 \tabularnewline
4 & 134.399166666667 & 2.34391459018041 & 10.0600000000000 \tabularnewline
5 & 136.870833333333 & 2.36897545301122 & 8.36000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28265&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]108.734166666667[/C][C]2.318069174328[/C][C]9.08[/C][/ROW]
[ROW][C]2[/C][C]118.065833333333[/C][C]2.89409259867354[/C][C]9.45[/C][/ROW]
[ROW][C]3[/C][C]130.965[/C][C]3.73951990112489[/C][C]11.93[/C][/ROW]
[ROW][C]4[/C][C]134.399166666667[/C][C]2.34391459018041[/C][C]10.0600000000000[/C][/ROW]
[ROW][C]5[/C][C]136.870833333333[/C][C]2.36897545301122[/C][C]8.36000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28265&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28265&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1108.7341666666672.3180691743289.08
2118.0658333333332.894092598673549.45
3130.9653.7395199011248911.93
4134.3991666666672.3439145901804110.0600000000000
5136.8708333333332.368975453011228.36000000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.93150421043656
beta0.00637015534133279
S.D.0.0292290531566525
T-STAT0.217939161668771
p-value0.84145904957214

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.93150421043656 \tabularnewline
beta & 0.00637015534133279 \tabularnewline
S.D. & 0.0292290531566525 \tabularnewline
T-STAT & 0.217939161668771 \tabularnewline
p-value & 0.84145904957214 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28265&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.93150421043656[/C][/ROW]
[ROW][C]beta[/C][C]0.00637015534133279[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0292290531566525[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.217939161668771[/C][/ROW]
[ROW][C]p-value[/C][C]0.84145904957214[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28265&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28265&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.93150421043656
beta0.00637015534133279
S.D.0.0292290531566525
T-STAT0.217939161668771
p-value0.84145904957214






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.329306045732420
beta0.272539541642196
S.D.1.20984352069164
T-STAT0.225268422718329
p-value0.836243436613135
Lambda0.727460458357804

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.329306045732420 \tabularnewline
beta & 0.272539541642196 \tabularnewline
S.D. & 1.20984352069164 \tabularnewline
T-STAT & 0.225268422718329 \tabularnewline
p-value & 0.836243436613135 \tabularnewline
Lambda & 0.727460458357804 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28265&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.329306045732420[/C][/ROW]
[ROW][C]beta[/C][C]0.272539541642196[/C][/ROW]
[ROW][C]S.D.[/C][C]1.20984352069164[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.225268422718329[/C][/ROW]
[ROW][C]p-value[/C][C]0.836243436613135[/C][/ROW]
[ROW][C]Lambda[/C][C]0.727460458357804[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28265&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28265&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.329306045732420
beta0.272539541642196
S.D.1.20984352069164
T-STAT0.225268422718329
p-value0.836243436613135
Lambda0.727460458357804


Figures (Output of Computation)

Input Parameters & R Code

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')