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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 01 Dec 2010 19:14:10 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/01/t1291230845ricjoxsgi8wtyz5.htm/, Retrieved Sun, 05 May 2024 16:37:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104169, Retrieved Sun, 05 May 2024 16:37:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact190

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] [Opgave 8 Oefening...] [2010-12-01 19:14:10] [93d384e9a6425954483697e7ea0f3a20] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.23
105.22
105.13
105
105.01
105.01
105.01
105.01
105.57
106.05
106.09
106.2
106.19
106.2
106.09
106.23
106.23
106.22
106.22
106.61
106.95
107.74
107.8
107.8
107.2
107.56
107.72
108.14
108.16
108.16
108.16
108.1
108.95
110.49
110.72
110.82
110.82
110.75
110.71
110.86
110.84
110.84
110.84
110.92
111.46
112.46
113.04
113.15
113.15
113.21
113.37
113.47
113.71
113.71
113.71
113.8
115.46
117
117.94
118.08
118.08
118.47
118.49
118.45
118.54
118.55
118.55
118.55
119.04
121.37
122
122.14

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'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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104169&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104169&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104169&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1105.37750.4732887836482841.20000000000000
2106.690.6977756868012141.70999999999999
3108.6816666666671.275495150436833.61999999999999
4111.3908333333330.9330347195462722.44000000000001
5114.71751.89354465583374.92999999999999
6119.35251.522438982207654.06

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 105.3775 & 0.473288783648284 & 1.20000000000000 \tabularnewline
2 & 106.69 & 0.697775686801214 & 1.70999999999999 \tabularnewline
3 & 108.681666666667 & 1.27549515043683 & 3.61999999999999 \tabularnewline
4 & 111.390833333333 & 0.933034719546272 & 2.44000000000001 \tabularnewline
5 & 114.7175 & 1.8935446558337 & 4.92999999999999 \tabularnewline
6 & 119.3525 & 1.52243898220765 & 4.06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104169&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]105.3775[/C][C]0.473288783648284[/C][C]1.20000000000000[/C][/ROW]
[ROW][C]2[/C][C]106.69[/C][C]0.697775686801214[/C][C]1.70999999999999[/C][/ROW]
[ROW][C]3[/C][C]108.681666666667[/C][C]1.27549515043683[/C][C]3.61999999999999[/C][/ROW]
[ROW][C]4[/C][C]111.390833333333[/C][C]0.933034719546272[/C][C]2.44000000000001[/C][/ROW]
[ROW][C]5[/C][C]114.7175[/C][C]1.8935446558337[/C][C]4.92999999999999[/C][/ROW]
[ROW][C]6[/C][C]119.3525[/C][C]1.52243898220765[/C][C]4.06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104169&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104169&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
1105.37750.4732887836482841.20000000000000
2106.690.6977756868012141.70999999999999
3108.6816666666671.275495150436833.61999999999999
4111.3908333333330.9330347195462722.44000000000001
5114.71751.89354465583374.92999999999999
6119.35251.522438982207654.06






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-7.84053353087098
beta0.0808135260108672
S.D.0.0301155257273952
T-STAT2.68345061422432
p-value0.0550309458887353

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -7.84053353087098 \tabularnewline
beta & 0.0808135260108672 \tabularnewline
S.D. & 0.0301155257273952 \tabularnewline
T-STAT & 2.68345061422432 \tabularnewline
p-value & 0.0550309458887353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104169&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.84053353087098[/C][/ROW]
[ROW][C]beta[/C][C]0.0808135260108672[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0301155257273952[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.68345061422432[/C][/ROW]
[ROW][C]p-value[/C][C]0.0550309458887353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104169&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104169&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)
alpha-7.84053353087098
beta0.0808135260108672
S.D.0.0301155257273952
T-STAT2.68345061422432
p-value0.0550309458887353






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-42.2255561478457
beta8.97156911376486
S.D.3.16361186048999
T-STAT2.83586277628107
p-value0.0470644700817523
Lambda-7.97156911376486

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -42.2255561478457 \tabularnewline
beta & 8.97156911376486 \tabularnewline
S.D. & 3.16361186048999 \tabularnewline
T-STAT & 2.83586277628107 \tabularnewline
p-value & 0.0470644700817523 \tabularnewline
Lambda & -7.97156911376486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104169&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-42.2255561478457[/C][/ROW]
[ROW][C]beta[/C][C]8.97156911376486[/C][/ROW]
[ROW][C]S.D.[/C][C]3.16361186048999[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.83586277628107[/C][/ROW]
[ROW][C]p-value[/C][C]0.0470644700817523[/C][/ROW]
[ROW][C]Lambda[/C][C]-7.97156911376486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104169&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104169&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-42.2255561478457
beta8.97156911376486
S.D.3.16361186048999
T-STAT2.83586277628107
p-value0.0470644700817523
Lambda-7.97156911376486


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')