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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, 21 Aug 2013 04:56:07 -0400

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/2013/Aug/21/t13770756745z790d3gyg9f5l2.htm/, Retrieved Sat, 27 Apr 2024 08:00:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211308, Retrieved Sat, 27 Apr 2024 08:00:40 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Raedts Mathias

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] [Tijdreeks B - Sta...] [2013-08-21 08:56:07] [e2e43c39163d7563005e2a800525cced] [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	'Gwilym Jenkins' @ jenkins.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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211308&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211308&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	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	932.5	33.6087109920249	120
2	917.5	64.5438540134465	190
3	908.333333333333	99.7117056439425	370
4	896.666666666667	114.996706145187	430
5	882.5	132.673557000906	470
6	887.5	121.888548198008	460
7	890	129.544657094834	420
8	885.833333333333	137.408371673856	480
9	907.5	149.613137488293	510

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 932.5 & 33.6087109920249 & 120 \tabularnewline
2 & 917.5 & 64.5438540134465 & 190 \tabularnewline
3 & 908.333333333333 & 99.7117056439425 & 370 \tabularnewline
4 & 896.666666666667 & 114.996706145187 & 430 \tabularnewline
5 & 882.5 & 132.673557000906 & 470 \tabularnewline
6 & 887.5 & 121.888548198008 & 460 \tabularnewline
7 & 890 & 129.544657094834 & 420 \tabularnewline
8 & 885.833333333333 & 137.408371673856 & 480 \tabularnewline
9 & 907.5 & 149.613137488293 & 510 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211308&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]932.5[/C][C]33.6087109920249[/C][C]120[/C][/ROW]
[ROW][C]2[/C][C]917.5[/C][C]64.5438540134465[/C][C]190[/C][/ROW]
[ROW][C]3[/C][C]908.333333333333[/C][C]99.7117056439425[/C][C]370[/C][/ROW]
[ROW][C]4[/C][C]896.666666666667[/C][C]114.996706145187[/C][C]430[/C][/ROW]
[ROW][C]5[/C][C]882.5[/C][C]132.673557000906[/C][C]470[/C][/ROW]
[ROW][C]6[/C][C]887.5[/C][C]121.888548198008[/C][C]460[/C][/ROW]
[ROW][C]7[/C][C]890[/C][C]129.544657094834[/C][C]420[/C][/ROW]
[ROW][C]8[/C][C]885.833333333333[/C][C]137.408371673856[/C][C]480[/C][/ROW]
[ROW][C]9[/C][C]907.5[/C][C]149.613137488293[/C][C]510[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211308&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	932.5	33.6087109920249	120
2	917.5	64.5438540134465	190
3	908.333333333333	99.7117056439425	370
4	896.666666666667	114.996706145187	430
5	882.5	132.673557000906	470
6	887.5	121.888548198008	460
7	890	129.544657094834	420
8	885.833333333333	137.408371673856	480
9	907.5	149.613137488293	510

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1790.31046567037
beta	-1.86583411421782
S.D.	0.47337800275328
T-STAT	-3.94153108797974
p-value	0.00559235731747911

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1790.31046567037 \tabularnewline
beta & -1.86583411421782 \tabularnewline
S.D. & 0.47337800275328 \tabularnewline
T-STAT & -3.94153108797974 \tabularnewline
p-value & 0.00559235731747911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211308&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1790.31046567037[/C][/ROW]
[ROW][C]beta[/C][C]-1.86583411421782[/C][/ROW]
[ROW][C]S.D.[/C][C]0.47337800275328[/C][/ROW]
[ROW][C]T-STAT[/C][C]-3.94153108797974[/C][/ROW]
[ROW][C]p-value[/C][C]0.00559235731747911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211308&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	1790.31046567037
beta	-1.86583411421782
S.D.	0.47337800275328
T-STAT	-3.94153108797974
p-value	0.00559235731747911

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	154.725272411434
beta	-22.0647511103723
S.D.	5.15589428451188
T-STAT	-4.27951969004756
p-value	0.00365754072303344
Lambda	23.0647511103723

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 154.725272411434 \tabularnewline
beta & -22.0647511103723 \tabularnewline
S.D. & 5.15589428451188 \tabularnewline
T-STAT & -4.27951969004756 \tabularnewline
p-value & 0.00365754072303344 \tabularnewline
Lambda & 23.0647511103723 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211308&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]154.725272411434[/C][/ROW]
[ROW][C]beta[/C][C]-22.0647511103723[/C][/ROW]
[ROW][C]S.D.[/C][C]5.15589428451188[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.27951969004756[/C][/ROW]
[ROW][C]p-value[/C][C]0.00365754072303344[/C][/ROW]
[ROW][C]Lambda[/C][C]23.0647511103723[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211308&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211308&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	154.725272411434
beta	-22.0647511103723
S.D.	5.15589428451188
T-STAT	-4.27951969004756
p-value	0.00365754072303344
Lambda	23.0647511103723

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 22 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;

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