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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Wed, 18 Nov 2015 16:34:22 +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/2015/Nov/18/t1447864507lud6pnyb1suolda.htm/, Retrieved Tue, 14 May 2024 16:30:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283517, Retrieved Tue, 14 May 2024 16:30:52 +0000

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No (this computation is public)

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Estimated Impact

109

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2015-11-18 16:34:22] [002d4cc575a6d7b5895f2103ed304b4f] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283517&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283517&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283517&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	1 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	25533.4166666667	825.232910189969	2308
2	25517.5833333333	412.201728710003	1251
3	25178.9166666667	242.302012272938	667
4	26428	565.548969023582	1751
5	27641.5	309.972286151227	975
6	26937.75	447.505840490074	1411
7	25944.4166666667	521.141833483036	1771
8	25976.1666666667	1000.18224096987	2872
9	28618.25	407.627754653233	1062

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 25533.4166666667 & 825.232910189969 & 2308 \tabularnewline
2 & 25517.5833333333 & 412.201728710003 & 1251 \tabularnewline
3 & 25178.9166666667 & 242.302012272938 & 667 \tabularnewline
4 & 26428 & 565.548969023582 & 1751 \tabularnewline
5 & 27641.5 & 309.972286151227 & 975 \tabularnewline
6 & 26937.75 & 447.505840490074 & 1411 \tabularnewline
7 & 25944.4166666667 & 521.141833483036 & 1771 \tabularnewline
8 & 25976.1666666667 & 1000.18224096987 & 2872 \tabularnewline
9 & 28618.25 & 407.627754653233 & 1062 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283517&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]25533.4166666667[/C][C]825.232910189969[/C][C]2308[/C][/ROW]
[ROW][C]2[/C][C]25517.5833333333[/C][C]412.201728710003[/C][C]1251[/C][/ROW]
[ROW][C]3[/C][C]25178.9166666667[/C][C]242.302012272938[/C][C]667[/C][/ROW]
[ROW][C]4[/C][C]26428[/C][C]565.548969023582[/C][C]1751[/C][/ROW]
[ROW][C]5[/C][C]27641.5[/C][C]309.972286151227[/C][C]975[/C][/ROW]
[ROW][C]6[/C][C]26937.75[/C][C]447.505840490074[/C][C]1411[/C][/ROW]
[ROW][C]7[/C][C]25944.4166666667[/C][C]521.141833483036[/C][C]1771[/C][/ROW]
[ROW][C]8[/C][C]25976.1666666667[/C][C]1000.18224096987[/C][C]2872[/C][/ROW]
[ROW][C]9[/C][C]28618.25[/C][C]407.627754653233[/C][C]1062[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283517&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283517&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	25533.4166666667	825.232910189969	2308
2	25517.5833333333	412.201728710003	1251
3	25178.9166666667	242.302012272938	667
4	26428	565.548969023582	1751
5	27641.5	309.972286151227	975
6	26937.75	447.505840490074	1411
7	25944.4166666667	521.141833483036	1771
8	25976.1666666667	1000.18224096987	2872
9	28618.25	407.627754653233	1062

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2042.48121225693
beta	-0.0574095591412442
S.D.	0.0789179287412521
T-STAT	-0.727459020490421
p-value	0.490553968866953

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2042.48121225693 \tabularnewline
beta & -0.0574095591412442 \tabularnewline
S.D. & 0.0789179287412521 \tabularnewline
T-STAT & -0.727459020490421 \tabularnewline
p-value & 0.490553968866953 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283517&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2042.48121225693[/C][/ROW]
[ROW][C]beta[/C][C]-0.0574095591412442[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0789179287412521[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.727459020490421[/C][/ROW]
[ROW][C]p-value[/C][C]0.490553968866953[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283517&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283517&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	2042.48121225693
beta	-0.0574095591412442
S.D.	0.0789179287412521
T-STAT	-0.727459020490421
p-value	0.490553968866953

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	26.6511584791437
beta	-2.01114875130989
S.D.	3.92672957054296
T-STAT	-0.512168896579197
p-value	0.624291839917892
Lambda	3.01114875130989

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 26.6511584791437 \tabularnewline
beta & -2.01114875130989 \tabularnewline
S.D. & 3.92672957054296 \tabularnewline
T-STAT & -0.512168896579197 \tabularnewline
p-value & 0.624291839917892 \tabularnewline
Lambda & 3.01114875130989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283517&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]26.6511584791437[/C][/ROW]
[ROW][C]beta[/C][C]-2.01114875130989[/C][/ROW]
[ROW][C]S.D.[/C][C]3.92672957054296[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.512168896579197[/C][/ROW]
[ROW][C]p-value[/C][C]0.624291839917892[/C][/ROW]
[ROW][C]Lambda[/C][C]3.01114875130989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283517&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283517&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	26.6511584791437
beta	-2.01114875130989
S.D.	3.92672957054296
T-STAT	-0.512168896579197
p-value	0.624291839917892
Lambda	3.01114875130989

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code