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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, 04 Aug 2010 11:26:24 +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/Aug/04/t1280921174g8u8bub2pf0a1yg.htm/, Retrieved Fri, 03 May 2024 08:21:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=78297, Retrieved Fri, 03 May 2024 08:21:02 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Bogaerts Yannik

Estimated Impact

155

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

-       [Standard Deviation-Mean Plot] [Tijdreeks A stap 26] [2010-08-04 11:26:24] [1596366c2ece8f787477cc7d1246d4c7] [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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78297&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78297&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

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	440.5	8.72301032275608	26
2	429.583333333333	18.7929306502270	58
3	408.75	14.4292946970580	48
4	383.166666666667	17.1243225922202	45
5	335.583333333333	28.9653659435268	77
6	283.583333333333	24.050924508155	73
7	243.083333333333	20.7428337387916	65
8	198.75	21.3546886484614	65
9	138.833333333333	27.0885193170073	71
10	66.3333333333333	26.3622779169346	72

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 440.5 & 8.72301032275608 & 26 \tabularnewline
2 & 429.583333333333 & 18.7929306502270 & 58 \tabularnewline
3 & 408.75 & 14.4292946970580 & 48 \tabularnewline
4 & 383.166666666667 & 17.1243225922202 & 45 \tabularnewline
5 & 335.583333333333 & 28.9653659435268 & 77 \tabularnewline
6 & 283.583333333333 & 24.050924508155 & 73 \tabularnewline
7 & 243.083333333333 & 20.7428337387916 & 65 \tabularnewline
8 & 198.75 & 21.3546886484614 & 65 \tabularnewline
9 & 138.833333333333 & 27.0885193170073 & 71 \tabularnewline
10 & 66.3333333333333 & 26.3622779169346 & 72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78297&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]440.5[/C][C]8.72301032275608[/C][C]26[/C][/ROW]
[ROW][C]2[/C][C]429.583333333333[/C][C]18.7929306502270[/C][C]58[/C][/ROW]
[ROW][C]3[/C][C]408.75[/C][C]14.4292946970580[/C][C]48[/C][/ROW]
[ROW][C]4[/C][C]383.166666666667[/C][C]17.1243225922202[/C][C]45[/C][/ROW]
[ROW][C]5[/C][C]335.583333333333[/C][C]28.9653659435268[/C][C]77[/C][/ROW]
[ROW][C]6[/C][C]283.583333333333[/C][C]24.050924508155[/C][C]73[/C][/ROW]
[ROW][C]7[/C][C]243.083333333333[/C][C]20.7428337387916[/C][C]65[/C][/ROW]
[ROW][C]8[/C][C]198.75[/C][C]21.3546886484614[/C][C]65[/C][/ROW]
[ROW][C]9[/C][C]138.833333333333[/C][C]27.0885193170073[/C][C]71[/C][/ROW]
[ROW][C]10[/C][C]66.3333333333333[/C][C]26.3622779169346[/C][C]72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78297&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	440.5	8.72301032275608	26
2	429.583333333333	18.7929306502270	58
3	408.75	14.4292946970580	48
4	383.166666666667	17.1243225922202	45
5	335.583333333333	28.9653659435268	77
6	283.583333333333	24.050924508155	73
7	243.083333333333	20.7428337387916	65
8	198.75	21.3546886484614	65
9	138.833333333333	27.0885193170073	71
10	66.3333333333333	26.3622779169346	72

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	30.6699344142291
beta	-0.0338318091435437
S.D.	0.0122293568488509
T-STAT	-2.76644222273411
p-value	0.0244305111701265

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 30.6699344142291 \tabularnewline
beta & -0.0338318091435437 \tabularnewline
S.D. & 0.0122293568488509 \tabularnewline
T-STAT & -2.76644222273411 \tabularnewline
p-value & 0.0244305111701265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78297&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]30.6699344142291[/C][/ROW]
[ROW][C]beta[/C][C]-0.0338318091435437[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0122293568488509[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.76644222273411[/C][/ROW]
[ROW][C]p-value[/C][C]0.0244305111701265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78297&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78297&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	30.6699344142291
beta	-0.0338318091435437
S.D.	0.0122293568488509
T-STAT	-2.76644222273411
p-value	0.0244305111701265

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	4.92911993606456
beta	-0.350901439232108
S.D.	0.169957240561104
T-STAT	-2.06464542536480
p-value	0.072832507128313
Lambda	1.35090143923211

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 4.92911993606456 \tabularnewline
beta & -0.350901439232108 \tabularnewline
S.D. & 0.169957240561104 \tabularnewline
T-STAT & -2.06464542536480 \tabularnewline
p-value & 0.072832507128313 \tabularnewline
Lambda & 1.35090143923211 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=78297&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.92911993606456[/C][/ROW]
[ROW][C]beta[/C][C]-0.350901439232108[/C][/ROW]
[ROW][C]S.D.[/C][C]0.169957240561104[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.06464542536480[/C][/ROW]
[ROW][C]p-value[/C][C]0.072832507128313[/C][/ROW]
[ROW][C]Lambda[/C][C]1.35090143923211[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=78297&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=78297&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	4.92911993606456
beta	-0.350901439232108
S.D.	0.169957240561104
T-STAT	-2.06464542536480
p-value	0.072832507128313
Lambda	1.35090143923211

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