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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 computationTue, 12 Jan 2010 11:15:33 -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/2010/Jan/12/t1263320277fg2x0oq5ahmhf04.htm/, Retrieved Tue, 07 May 2024 18:23:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=72109, Retrieved Tue, 07 May 2024 18:23:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact110

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] [VERBETERING Opgav...] [2010-01-12 18:15:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10,1200
10,1200
10,0500
10,1400
10,1700
10,2000
10,2000
10,3500
10,4300
10,5200
10,5700
10,5700
10,5700
10,6500
10,5700
10,6100
10,6300
10,7100
10,7200
10,7700
10,7900
10,8200
10,9000
10,8300
10,9200
10,9100
10,8800
10,8700
11,0000
10,9900
11,0300
11,0400
10,9900
10,9000
11,0000
10,9900
10,9200
10,9800
11,1500
11,1900
11,3300
11,3800
11,4000
11,4500
11,5600
11,6100
11,8200
11,7700
11,8500
11,8200
11,9200
11,8600
11,8700
11,9400
11,8600
11,9200
11,8300
11,9100
11,9300
11,9900
11,9600
12,1200
11,8500
12,0100
12,1000
12,2100
12,3100
12,3100
12,3900
12,3500
12,4100
12,5100

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72109&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]2 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=72109&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72109&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
110.28666666666670.1909942090189850.52
210.71416666666670.1094164964572060.33
310.960.05984829305684630.17
411.380.2859434146184110.9
511.89166666666670.05096047190685840.17
612.21083333333330.2032221504271680.66

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10.2866666666667 & 0.190994209018985 & 0.52 \tabularnewline
2 & 10.7141666666667 & 0.109416496457206 & 0.33 \tabularnewline
3 & 10.96 & 0.0598482930568463 & 0.17 \tabularnewline
4 & 11.38 & 0.285943414618411 & 0.9 \tabularnewline
5 & 11.8916666666667 & 0.0509604719068584 & 0.17 \tabularnewline
6 & 12.2108333333333 & 0.203222150427168 & 0.66 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72109&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]10.2866666666667[/C][C]0.190994209018985[/C][C]0.52[/C][/ROW]
[ROW][C]2[/C][C]10.7141666666667[/C][C]0.109416496457206[/C][C]0.33[/C][/ROW]
[ROW][C]3[/C][C]10.96[/C][C]0.0598482930568463[/C][C]0.17[/C][/ROW]
[ROW][C]4[/C][C]11.38[/C][C]0.285943414618411[/C][C]0.9[/C][/ROW]
[ROW][C]5[/C][C]11.8916666666667[/C][C]0.0509604719068584[/C][C]0.17[/C][/ROW]
[ROW][C]6[/C][C]12.2108333333333[/C][C]0.203222150427168[/C][C]0.66[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72109&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72109&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
110.28666666666670.1909942090189850.52
210.71416666666670.1094164964572060.33
310.960.05984829305684630.17
411.380.2859434146184110.9
511.89166666666670.05096047190685840.17
612.21083333333330.2032221504271680.66






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.092123557215992
beta0.00515460424340714
S.D.0.0633185741117288
T-STAT0.0814074592758768
p-value0.939028556255687

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.092123557215992 \tabularnewline
beta & 0.00515460424340714 \tabularnewline
S.D. & 0.0633185741117288 \tabularnewline
T-STAT & 0.0814074592758768 \tabularnewline
p-value & 0.939028556255687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72109&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.092123557215992[/C][/ROW]
[ROW][C]beta[/C][C]0.00515460424340714[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0633185741117288[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0814074592758768[/C][/ROW]
[ROW][C]p-value[/C][C]0.939028556255687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72109&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72109&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)
alpha0.092123557215992
beta0.00515460424340714
S.D.0.0633185741117288
T-STAT0.0814074592758768
p-value0.939028556255687






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.616280428279707
beta-0.607201890419071
S.D.5.41421878769374
T-STAT-0.112149492702292
p-value0.916107555435064
Lambda1.60720189041907

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.616280428279707 \tabularnewline
beta & -0.607201890419071 \tabularnewline
S.D. & 5.41421878769374 \tabularnewline
T-STAT & -0.112149492702292 \tabularnewline
p-value & 0.916107555435064 \tabularnewline
Lambda & 1.60720189041907 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=72109&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.616280428279707[/C][/ROW]
[ROW][C]beta[/C][C]-0.607201890419071[/C][/ROW]
[ROW][C]S.D.[/C][C]5.41421878769374[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.112149492702292[/C][/ROW]
[ROW][C]p-value[/C][C]0.916107555435064[/C][/ROW]
[ROW][C]Lambda[/C][C]1.60720189041907[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=72109&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=72109&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-0.616280428279707
beta-0.607201890419071
S.D.5.41421878769374
T-STAT-0.112149492702292
p-value0.916107555435064
Lambda1.60720189041907


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')