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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

Mon, 20 Jul 2015 12:50:52 +0100

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/Jul/20/t1437393304q5iva4iovx09f3x.htm/, Retrieved Fri, 17 May 2024 06:59:47 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279604, Retrieved Fri, 17 May 2024 06:59:47 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

158

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

-     [(Partial) Autocorrelation Function] [STAP 20 Omzet vorken] [2015-07-20 11:10:10] [110a48b2e0105bb86f6db58fdf2bbafc]
- RMP     [Standard Deviation-Mean Plot] [STAP 26 Omzet vorken] [2015-07-20 11:50:52] [70d22f55a70f3427b60459805adf1606] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279604&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279604&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279604&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	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	208.506833333333	7.06594567862882	21.076
2	212.1515	7.4974436309985	24.288
3	217.688166666667	7.35403768914283	23.507
4	224.641083333333	7.52415856314401	25.938
5	217.832083333333	12.390486273078	44.517
6	198.26125	14.7727867631669	51.018
7	178.349416666667	12.1488001911026	43.725
8	151.152833333333	16.9326970188843	61.512
9	131.783666666667	18.9076275437542	63.162
10	105.05825	20.9255292107512	72.094

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 208.506833333333 & 7.06594567862882 & 21.076 \tabularnewline
2 & 212.1515 & 7.4974436309985 & 24.288 \tabularnewline
3 & 217.688166666667 & 7.35403768914283 & 23.507 \tabularnewline
4 & 224.641083333333 & 7.52415856314401 & 25.938 \tabularnewline
5 & 217.832083333333 & 12.390486273078 & 44.517 \tabularnewline
6 & 198.26125 & 14.7727867631669 & 51.018 \tabularnewline
7 & 178.349416666667 & 12.1488001911026 & 43.725 \tabularnewline
8 & 151.152833333333 & 16.9326970188843 & 61.512 \tabularnewline
9 & 131.783666666667 & 18.9076275437542 & 63.162 \tabularnewline
10 & 105.05825 & 20.9255292107512 & 72.094 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279604&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]208.506833333333[/C][C]7.06594567862882[/C][C]21.076[/C][/ROW]
[ROW][C]2[/C][C]212.1515[/C][C]7.4974436309985[/C][C]24.288[/C][/ROW]
[ROW][C]3[/C][C]217.688166666667[/C][C]7.35403768914283[/C][C]23.507[/C][/ROW]
[ROW][C]4[/C][C]224.641083333333[/C][C]7.52415856314401[/C][C]25.938[/C][/ROW]
[ROW][C]5[/C][C]217.832083333333[/C][C]12.390486273078[/C][C]44.517[/C][/ROW]
[ROW][C]6[/C][C]198.26125[/C][C]14.7727867631669[/C][C]51.018[/C][/ROW]
[ROW][C]7[/C][C]178.349416666667[/C][C]12.1488001911026[/C][C]43.725[/C][/ROW]
[ROW][C]8[/C][C]151.152833333333[/C][C]16.9326970188843[/C][C]61.512[/C][/ROW]
[ROW][C]9[/C][C]131.783666666667[/C][C]18.9076275437542[/C][C]63.162[/C][/ROW]
[ROW][C]10[/C][C]105.05825[/C][C]20.9255292107512[/C][C]72.094[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279604&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279604&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	208.506833333333	7.06594567862882	21.076
2	212.1515	7.4974436309985	24.288
3	217.688166666667	7.35403768914283	23.507
4	224.641083333333	7.52415856314401	25.938
5	217.832083333333	12.390486273078	44.517
6	198.26125	14.7727867631669	51.018
7	178.349416666667	12.1488001911026	43.725
8	151.152833333333	16.9326970188843	61.512
9	131.783666666667	18.9076275437542	63.162
10	105.05825	20.9255292107512	72.094

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	33.4332668148062
beta	-0.113151792219188
S.D.	0.0185894327362385
T-STAT	-6.08688784777213
p-value	0.000293686871073615

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 33.4332668148062 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362385 \tabularnewline
T-STAT & -6.08688784777213 \tabularnewline
p-value & 0.000293686871073615 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279604&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]33.4332668148062[/C][/ROW]
[ROW][C]beta[/C][C]-0.113151792219188[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0185894327362385[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.08688784777213[/C][/ROW]
[ROW][C]p-value[/C][C]0.000293686871073615[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279604&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279604&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	33.4332668148062
beta	-0.113151792219188
S.D.	0.0185894327362385
T-STAT	-6.08688784777213
p-value	0.000293686871073615

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	9.64357959445596
beta	-1.38589065989076
S.D.	0.316605261909547
T-STAT	-4.37734563074542
p-value	0.00235715681397511
Lambda	2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.64357959445596 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.316605261909547 \tabularnewline
T-STAT & -4.37734563074542 \tabularnewline
p-value & 0.00235715681397511 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279604&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.64357959445596[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.316605261909547[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074542[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397511[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279604&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279604&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	9.64357959445596
beta	-1.38589065989076
S.D.	0.316605261909547
T-STAT	-4.37734563074542
p-value	0.00235715681397511
Lambda	2.38589065989076

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