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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, 29 Dec 2010 15:06:08 +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/29/t1293635041evtwsb6vqgjipee.htm/, Retrieved Fri, 03 May 2024 05:24:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116896, Retrieved Fri, 03 May 2024 05:24:37 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

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Estimated Impact

112

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

-       [Standard Deviation-Mean Plot] [Paper] [2010-12-29 15:06:08] [d5e0edb7e0239841e94676417b2a1e2e] [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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
R Framework error message & Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116896&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[ROW][C]R Framework error message[/C][C]Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116896&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
R Framework error message	Warning: there are blank lines in the 'Data' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	1001.91666666667	46.1488861942485	140
2	1441.16666666667	159.605669376027	455
3	1565.33333333333	46.4881868344154	135
4	1310.33333333333	111.594504046272	294
5	1334	72.5822417550038	216

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1001.91666666667 & 46.1488861942485 & 140 \tabularnewline
2 & 1441.16666666667 & 159.605669376027 & 455 \tabularnewline
3 & 1565.33333333333 & 46.4881868344154 & 135 \tabularnewline
4 & 1310.33333333333 & 111.594504046272 & 294 \tabularnewline
5 & 1334 & 72.5822417550038 & 216 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116896&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]1001.91666666667[/C][C]46.1488861942485[/C][C]140[/C][/ROW]
[ROW][C]2[/C][C]1441.16666666667[/C][C]159.605669376027[/C][C]455[/C][/ROW]
[ROW][C]3[/C][C]1565.33333333333[/C][C]46.4881868344154[/C][C]135[/C][/ROW]
[ROW][C]4[/C][C]1310.33333333333[/C][C]111.594504046272[/C][C]294[/C][/ROW]
[ROW][C]5[/C][C]1334[/C][C]72.5822417550038[/C][C]216[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116896&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	1001.91666666667	46.1488861942485	140
2	1441.16666666667	159.605669376027	455
3	1565.33333333333	46.4881868344154	135
4	1310.33333333333	111.594504046272	294
5	1334	72.5822417550038	216

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1.00787535258491
beta	0.0648423751746333
S.D.	0.12811079950939
T-STAT	0.506142928019746
p-value	0.64760755784923

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.00787535258491 \tabularnewline
beta & 0.0648423751746333 \tabularnewline
S.D. & 0.12811079950939 \tabularnewline
T-STAT & 0.506142928019746 \tabularnewline
p-value & 0.64760755784923 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116896&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.00787535258491[/C][/ROW]
[ROW][C]beta[/C][C]0.0648423751746333[/C][/ROW]
[ROW][C]S.D.[/C][C]0.12811079950939[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.506142928019746[/C][/ROW]
[ROW][C]p-value[/C][C]0.64760755784923[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116896&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116896&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	1.00787535258491
beta	0.0648423751746333
S.D.	0.12811079950939
T-STAT	0.506142928019746
p-value	0.64760755784923

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-3.02118464568844
beta	1.02607951834764
S.D.	1.77741796963512
T-STAT	0.577286567299802
p-value	0.604219234775545
Lambda	-0.0260795183476401

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.02118464568844 \tabularnewline
beta & 1.02607951834764 \tabularnewline
S.D. & 1.77741796963512 \tabularnewline
T-STAT & 0.577286567299802 \tabularnewline
p-value & 0.604219234775545 \tabularnewline
Lambda & -0.0260795183476401 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116896&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.02118464568844[/C][/ROW]
[ROW][C]beta[/C][C]1.02607951834764[/C][/ROW]
[ROW][C]S.D.[/C][C]1.77741796963512[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.577286567299802[/C][/ROW]
[ROW][C]p-value[/C][C]0.604219234775545[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.0260795183476401[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116896&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116896&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	-3.02118464568844
beta	1.02607951834764
S.D.	1.77741796963512
T-STAT	0.577286567299802
p-value	0.604219234775545
Lambda	-0.0260795183476401

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 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