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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Fri, 24 Dec 2010 15:28:33 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t12932044106c7r2m9d3gy6gqx.htm/, Retrieved Tue, 30 Apr 2024 07:09:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115118, Retrieved Tue, 30 Apr 2024 07:09:50 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

108

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [] [2010-12-24 15:28:33] [5a59313293e5c9f616ad36f6edd018c5] [Current]

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Dataseries X:

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Histogram

Boxplots

1.35
1.91
1.31
1.19
1.3
1.14
1.1
1.02
1.11
1.18
1.24
1.36
1.29
1.73
1.41
1.15
1.31
1.15
1.08
1.1
1.14
1.24
1.33
1.49
1.38
1.96
1.36
1.24
1.35
1.23
1.09
1.08
1.33
1.35
1.38
1.5
1.47
2.09
1.52
1.29
1.52
1.27
1.35
1.29
1.41
1.39
1.45
1.53
1.45
2.11
1.53
1.38
1.54
1.35
1.29
1.33
1.47
1.47
1.54
1.59
1.5
2
1.51
1.4
1.62
1.44
1.29
1.28
1.4
1.39
1.46
1.49

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115118&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]3 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=115118&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115118&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.2675	0.228796257121325	0.89
2	1.285	0.189280935984776	0.65
3	1.35416666666667	0.226372915715854	0.88
4	1.465	0.217903231233082	0.82
5	1.50416666666667	0.212836186829783	0.82
6	1.48166666666667	0.188382267710841	0.72

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.2675 & 0.228796257121325 & 0.89 \tabularnewline
2 & 1.285 & 0.189280935984776 & 0.65 \tabularnewline
3 & 1.35416666666667 & 0.226372915715854 & 0.88 \tabularnewline
4 & 1.465 & 0.217903231233082 & 0.82 \tabularnewline
5 & 1.50416666666667 & 0.212836186829783 & 0.82 \tabularnewline
6 & 1.48166666666667 & 0.188382267710841 & 0.72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115118&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]1.2675[/C][C]0.228796257121325[/C][C]0.89[/C][/ROW]
[ROW][C]2[/C][C]1.285[/C][C]0.189280935984776[/C][C]0.65[/C][/ROW]
[ROW][C]3[/C][C]1.35416666666667[/C][C]0.226372915715854[/C][C]0.88[/C][/ROW]
[ROW][C]4[/C][C]1.465[/C][C]0.217903231233082[/C][C]0.82[/C][/ROW]
[ROW][C]5[/C][C]1.50416666666667[/C][C]0.212836186829783[/C][C]0.82[/C][/ROW]
[ROW][C]6[/C][C]1.48166666666667[/C][C]0.188382267710841[/C][C]0.72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115118&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115118&T=1

As an alternative you can also use a QR Code:

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

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1.2675	0.228796257121325	0.89
2	1.285	0.189280935984776	0.65
3	1.35416666666667	0.226372915715854	0.88
4	1.465	0.217903231233082	0.82
5	1.50416666666667	0.212836186829783	0.82
6	1.48166666666667	0.188382267710841	0.72

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.256471281175055
beta	-0.0329351950289766
S.D.	0.0838390337464429
T-STAT	-0.39283843762541
p-value	0.714475122566236

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.256471281175055 \tabularnewline
beta & -0.0329351950289766 \tabularnewline
S.D. & 0.0838390337464429 \tabularnewline
T-STAT & -0.39283843762541 \tabularnewline
p-value & 0.714475122566236 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115118&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.256471281175055[/C][/ROW]
[ROW][C]beta[/C][C]-0.0329351950289766[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0838390337464429[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.39283843762541[/C][/ROW]
[ROW][C]p-value[/C][C]0.714475122566236[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115118&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115118&T=2

As an alternative you can also use a QR Code:

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

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.256471281175055
beta	-0.0329351950289766
S.D.	0.0838390337464429
T-STAT	-0.39283843762541
p-value	0.714475122566236

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.49550748611395
beta	-0.198653183010635
S.D.	0.562600584302969
T-STAT	-0.353098074465663
p-value	0.74183728898751
Lambda	1.19865318301064

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.49550748611395 \tabularnewline
beta & -0.198653183010635 \tabularnewline
S.D. & 0.562600584302969 \tabularnewline
T-STAT & -0.353098074465663 \tabularnewline
p-value & 0.74183728898751 \tabularnewline
Lambda & 1.19865318301064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115118&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.49550748611395[/C][/ROW]
[ROW][C]beta[/C][C]-0.198653183010635[/C][/ROW]
[ROW][C]S.D.[/C][C]0.562600584302969[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.353098074465663[/C][/ROW]
[ROW][C]p-value[/C][C]0.74183728898751[/C][/ROW]
[ROW][C]Lambda[/C][C]1.19865318301064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115118&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115118&T=3

As an alternative you can also use a QR Code:

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

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.49550748611395
beta	-0.198653183010635
S.D.	0.562600584302969
T-STAT	-0.353098074465663
p-value	0.74183728898751
Lambda	1.19865318301064

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code