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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 computationMon, 01 Jun 2009 13:06:36 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jun/01/t1243883360syrxq7fasn9grzd.htm/, Retrieved Sun, 12 May 2024 17:11:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41047, Retrieved Sun, 12 May 2024 17:11:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

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] [thomas van eester...] [2009-06-01 19:06:36] [95fcaf7e4175e3dfad928879b5f9d7c2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.63
0.63
0.63
0.64
0.63
0.63
0.63
0.63
0.63
0.64
0.65
0.65
0.65
0.65
0.65
0.66
0.65
0.66
0.66
0.66
0.66
0.68
0.69
0.7
0.71
0.71
0.7
0.7
0.7
0.7
0.71
0.7
0.7
0.7
0.69
0.7
0.69
0.69
0.69
0.7
0.7
0.71
0.71
0.71
0.72
0.73
0.74
0.74
0.74
0.74
0.75
0.75
0.76
0.76
0.76
0.76
0.76
0.77
0.77
0.78
0.78
0.78
0.78
0.78
0.78
0.78
0.8
0.8
0.8
0.81
0.81
0.81
0.8
0.81
0.81
0.81
0.8
0.82
0.83
0.83

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=41047&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=41047&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41047&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
10.6350.007977240352174660.02
20.6641666666666670.01676486224400920.0499999999999999
30.7016666666666670.005773502691896260.02
40.7108333333333330.01831955405041460.05
50.7583333333333330.01193416282879710.04
60.79250.01356801050599940.03

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.635 & 0.00797724035217466 & 0.02 \tabularnewline
2 & 0.664166666666667 & 0.0167648622440092 & 0.0499999999999999 \tabularnewline
3 & 0.701666666666667 & 0.00577350269189626 & 0.02 \tabularnewline
4 & 0.710833333333333 & 0.0183195540504146 & 0.05 \tabularnewline
5 & 0.758333333333333 & 0.0119341628287971 & 0.04 \tabularnewline
6 & 0.7925 & 0.0135680105059994 & 0.03 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41047&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]0.635[/C][C]0.00797724035217466[/C][C]0.02[/C][/ROW]
[ROW][C]2[/C][C]0.664166666666667[/C][C]0.0167648622440092[/C][C]0.0499999999999999[/C][/ROW]
[ROW][C]3[/C][C]0.701666666666667[/C][C]0.00577350269189626[/C][C]0.02[/C][/ROW]
[ROW][C]4[/C][C]0.710833333333333[/C][C]0.0183195540504146[/C][C]0.05[/C][/ROW]
[ROW][C]5[/C][C]0.758333333333333[/C][C]0.0119341628287971[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]0.7925[/C][C]0.0135680105059994[/C][C]0.03[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41047&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41047&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
10.6350.007977240352174660.02
20.6641666666666670.01676486224400920.0499999999999999
30.7016666666666670.005773502691896260.02
40.7108333333333330.01831955405041460.05
50.7583333333333330.01193416282879710.04
60.79250.01356801050599940.03






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.00124596395777943
beta0.0156859938830767
S.D.0.0411961331881814
T-STAT0.380763743320862
p-value0.722736747515292

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.00124596395777943 \tabularnewline
beta & 0.0156859938830767 \tabularnewline
S.D. & 0.0411961331881814 \tabularnewline
T-STAT & 0.380763743320862 \tabularnewline
p-value & 0.722736747515292 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41047&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.00124596395777943[/C][/ROW]
[ROW][C]beta[/C][C]0.0156859938830767[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0411961331881814[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.380763743320862[/C][/ROW]
[ROW][C]p-value[/C][C]0.722736747515292[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41047&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41047&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)
alpha0.00124596395777943
beta0.0156859938830767
S.D.0.0411961331881814
T-STAT0.380763743320862
p-value0.722736747515292






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.00376077959871
beta1.34405426970411
S.D.2.64457269029384
T-STAT0.508231168928378
p-value0.638037664075083
Lambda-0.344054269704106

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.00376077959871 \tabularnewline
beta & 1.34405426970411 \tabularnewline
S.D. & 2.64457269029384 \tabularnewline
T-STAT & 0.508231168928378 \tabularnewline
p-value & 0.638037664075083 \tabularnewline
Lambda & -0.344054269704106 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41047&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.00376077959871[/C][/ROW]
[ROW][C]beta[/C][C]1.34405426970411[/C][/ROW]
[ROW][C]S.D.[/C][C]2.64457269029384[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.508231168928378[/C][/ROW]
[ROW][C]p-value[/C][C]0.638037664075083[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.344054269704106[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41047&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41047&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-4.00376077959871
beta1.34405426970411
S.D.2.64457269029384
T-STAT0.508231168928378
p-value0.638037664075083
Lambda-0.344054269704106


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')