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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 computationThu, 29 Nov 2007 06:03:36 -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/29/t1196340848qe2dtftz4ub8dvp.htm/, Retrieved Fri, 03 May 2024 09:19:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7458, Retrieved Fri, 03 May 2024 09:19:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop stationarity in time series
Estimated Impact172

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] [standard deviatio...] [2007-11-29 13:03:36] [7eb5b05bf0841f2a6d4b99da83be8d69] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,52
103,5
103,52
103,53
103,53
103,53
103,52
103,54
103,59
103,59
103,59
103,59
103,63
103,74
103,7
103,72
103,81
103,8
104,22
106,91
107,06
107,17
107,25
107,28
107,24
107,23
107,34
107,34
107,3
107,24
107,3
107,32
107,28
107,33
107,33
107,33
107,28
107,28
107,29
107,29
107,23
107,24
107,24
107,2
107,23
107,2
107,21
107,24
107,21
113,89
114,05
114,05
114,05
114,05
115,12
115,68
116,05
116,18
116,35
116,44
117
117,61
118,17
118,33
118,33
118,42
118,5
118,67
119,09
119,14
119,23
119,33

Tables (Output of Computation)





Summary of compuational 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 compuational 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=7458&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]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=7458&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7458&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 compuational 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
1103.5458333333330.03396745322787720.0700000000000074
2105.1908333333331.723682412918943.78
3107.2983333333330.04130448651249233.82000000000001
4107.2441666666670.03342789617107763.76000000000001
5114.4266666666672.4945297728988512.91
6118.4850.68893197975364315.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.545833333333 & 0.0339674532278772 & 0.0700000000000074 \tabularnewline
2 & 105.190833333333 & 1.72368241291894 & 3.78 \tabularnewline
3 & 107.298333333333 & 0.0413044865124923 & 3.82000000000001 \tabularnewline
4 & 107.244166666667 & 0.0334278961710776 & 3.76000000000001 \tabularnewline
5 & 114.426666666667 & 2.49452977289885 & 12.91 \tabularnewline
6 & 118.485 & 0.688931979753643 & 15.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7458&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]103.545833333333[/C][C]0.0339674532278772[/C][C]0.0700000000000074[/C][/ROW]
[ROW][C]2[/C][C]105.190833333333[/C][C]1.72368241291894[/C][C]3.78[/C][/ROW]
[ROW][C]3[/C][C]107.298333333333[/C][C]0.0413044865124923[/C][C]3.82000000000001[/C][/ROW]
[ROW][C]4[/C][C]107.244166666667[/C][C]0.0334278961710776[/C][C]3.76000000000001[/C][/ROW]
[ROW][C]5[/C][C]114.426666666667[/C][C]2.49452977289885[/C][C]12.91[/C][/ROW]
[ROW][C]6[/C][C]118.485[/C][C]0.688931979753643[/C][C]15.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7458&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7458&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
1103.5458333333330.03396745322787720.0700000000000074
2105.1908333333331.723682412918943.78
3107.2983333333330.04130448651249233.82000000000001
4107.2441666666670.03342789617107763.76000000000001
5114.4266666666672.4945297728988512.91
6118.4850.68893197975364315.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-6.52194197584137
beta0.0672784403772751
S.D.0.083552307424662
T-STAT0.805225402517329
p-value0.465829043926337

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -6.52194197584137 \tabularnewline
beta & 0.0672784403772751 \tabularnewline
S.D. & 0.083552307424662 \tabularnewline
T-STAT & 0.805225402517329 \tabularnewline
p-value & 0.465829043926337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7458&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-6.52194197584137[/C][/ROW]
[ROW][C]beta[/C][C]0.0672784403772751[/C][/ROW]
[ROW][C]S.D.[/C][C]0.083552307424662[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.805225402517329[/C][/ROW]
[ROW][C]p-value[/C][C]0.465829043926337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7458&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7458&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-6.52194197584137
beta0.0672784403772751
S.D.0.083552307424662
T-STAT0.805225402517329
p-value0.465829043926337






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-101.604564182508
beta21.3323702487885
S.D.16.5586243376863
T-STAT1.28829362957631
p-value0.267113917205727
Lambda-20.3323702487885

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -101.604564182508 \tabularnewline
beta & 21.3323702487885 \tabularnewline
S.D. & 16.5586243376863 \tabularnewline
T-STAT & 1.28829362957631 \tabularnewline
p-value & 0.267113917205727 \tabularnewline
Lambda & -20.3323702487885 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7458&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-101.604564182508[/C][/ROW]
[ROW][C]beta[/C][C]21.3323702487885[/C][/ROW]
[ROW][C]S.D.[/C][C]16.5586243376863[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.28829362957631[/C][/ROW]
[ROW][C]p-value[/C][C]0.267113917205727[/C][/ROW]
[ROW][C]Lambda[/C][C]-20.3323702487885[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7458&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7458&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-101.604564182508
beta21.3323702487885
S.D.16.5586243376863
T-STAT1.28829362957631
p-value0.267113917205727
Lambda-20.3323702487885


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')