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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

Tue, 17 Aug 2010 08:18:54 +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/17/t1282033116efyvbimr0sumv2f.htm/, Retrieved Sat, 27 Apr 2024 13:05:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=79058, Retrieved Sat, 27 Apr 2024 13:05:55 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

149

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B Stap ...] [2010-08-17 08:18:54] [5e78ed906b09bab42b8ec3dd93b6358a] [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=79058&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=79058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79058&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	91.25	1.70782512765993	4
2	87.25	1.25830573921179	3
3	91	1.41421356237310	3
4	90.25	2.75378527364305	6
5	92.25	4.5	11
6	98.25	4.5	10
7	92.75	6.5	15
8	91.5	9.46924847422786	22
9	110.75	9.5	20
10	108.5	5.97215762238964	14
11	114.75	9.74251849711699	23
12	132.25	9.17877987534291	22
13	127.25	10.7819293264239	26
14	138.25	3.77491721763537	9
15	150.25	7.8049129826454	18
16	129.75	13.0479883506999	30
17	133.75	4.5	11
18	138.25	14.2448821218944	33
19	131.25	10.2428837085396	22
20	146.75	0.957427107756338	2
21	156.25	17.3084757657436	41

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.25 & 1.70782512765993 & 4 \tabularnewline
2 & 87.25 & 1.25830573921179 & 3 \tabularnewline
3 & 91 & 1.41421356237310 & 3 \tabularnewline
4 & 90.25 & 2.75378527364305 & 6 \tabularnewline
5 & 92.25 & 4.5 & 11 \tabularnewline
6 & 98.25 & 4.5 & 10 \tabularnewline
7 & 92.75 & 6.5 & 15 \tabularnewline
8 & 91.5 & 9.46924847422786 & 22 \tabularnewline
9 & 110.75 & 9.5 & 20 \tabularnewline
10 & 108.5 & 5.97215762238964 & 14 \tabularnewline
11 & 114.75 & 9.74251849711699 & 23 \tabularnewline
12 & 132.25 & 9.17877987534291 & 22 \tabularnewline
13 & 127.25 & 10.7819293264239 & 26 \tabularnewline
14 & 138.25 & 3.77491721763537 & 9 \tabularnewline
15 & 150.25 & 7.8049129826454 & 18 \tabularnewline
16 & 129.75 & 13.0479883506999 & 30 \tabularnewline
17 & 133.75 & 4.5 & 11 \tabularnewline
18 & 138.25 & 14.2448821218944 & 33 \tabularnewline
19 & 131.25 & 10.2428837085396 & 22 \tabularnewline
20 & 146.75 & 0.957427107756338 & 2 \tabularnewline
21 & 156.25 & 17.3084757657436 & 41 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79058&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]91.25[/C][C]1.70782512765993[/C][C]4[/C][/ROW]
[ROW][C]2[/C][C]87.25[/C][C]1.25830573921179[/C][C]3[/C][/ROW]
[ROW][C]3[/C][C]91[/C][C]1.41421356237310[/C][C]3[/C][/ROW]
[ROW][C]4[/C][C]90.25[/C][C]2.75378527364305[/C][C]6[/C][/ROW]
[ROW][C]5[/C][C]92.25[/C][C]4.5[/C][C]11[/C][/ROW]
[ROW][C]6[/C][C]98.25[/C][C]4.5[/C][C]10[/C][/ROW]
[ROW][C]7[/C][C]92.75[/C][C]6.5[/C][C]15[/C][/ROW]
[ROW][C]8[/C][C]91.5[/C][C]9.46924847422786[/C][C]22[/C][/ROW]
[ROW][C]9[/C][C]110.75[/C][C]9.5[/C][C]20[/C][/ROW]
[ROW][C]10[/C][C]108.5[/C][C]5.97215762238964[/C][C]14[/C][/ROW]
[ROW][C]11[/C][C]114.75[/C][C]9.74251849711699[/C][C]23[/C][/ROW]
[ROW][C]12[/C][C]132.25[/C][C]9.17877987534291[/C][C]22[/C][/ROW]
[ROW][C]13[/C][C]127.25[/C][C]10.7819293264239[/C][C]26[/C][/ROW]
[ROW][C]14[/C][C]138.25[/C][C]3.77491721763537[/C][C]9[/C][/ROW]
[ROW][C]15[/C][C]150.25[/C][C]7.8049129826454[/C][C]18[/C][/ROW]
[ROW][C]16[/C][C]129.75[/C][C]13.0479883506999[/C][C]30[/C][/ROW]
[ROW][C]17[/C][C]133.75[/C][C]4.5[/C][C]11[/C][/ROW]
[ROW][C]18[/C][C]138.25[/C][C]14.2448821218944[/C][C]33[/C][/ROW]
[ROW][C]19[/C][C]131.25[/C][C]10.2428837085396[/C][C]22[/C][/ROW]
[ROW][C]20[/C][C]146.75[/C][C]0.957427107756338[/C][C]2[/C][/ROW]
[ROW][C]21[/C][C]156.25[/C][C]17.3084757657436[/C][C]41[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79058&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79058&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	91.25	1.70782512765993	4
2	87.25	1.25830573921179	3
3	91	1.41421356237310	3
4	90.25	2.75378527364305	6
5	92.25	4.5	11
6	98.25	4.5	10
7	92.75	6.5	15
8	91.5	9.46924847422786	22
9	110.75	9.5	20
10	108.5	5.97215762238964	14
11	114.75	9.74251849711699	23
12	132.25	9.17877987534291	22
13	127.25	10.7819293264239	26
14	138.25	3.77491721763537	9
15	150.25	7.8049129826454	18
16	129.75	13.0479883506999	30
17	133.75	4.5	11
18	138.25	14.2448821218944	33
19	131.25	10.2428837085396	22
20	146.75	0.957427107756338	2
21	156.25	17.3084757657436	41

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-4.94892235533765
beta	0.103195767671924
S.D.	0.039010279550324
T-STAT	2.64534806880325
p-value	0.0159593577711054

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.94892235533765 \tabularnewline
beta & 0.103195767671924 \tabularnewline
S.D. & 0.039010279550324 \tabularnewline
T-STAT & 2.64534806880325 \tabularnewline
p-value & 0.0159593577711054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79058&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.94892235533765[/C][/ROW]
[ROW][C]beta[/C][C]0.103195767671924[/C][/ROW]
[ROW][C]S.D.[/C][C]0.039010279550324[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.64534806880325[/C][/ROW]
[ROW][C]p-value[/C][C]0.0159593577711054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79058&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79058&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	-4.94892235533765
beta	0.103195767671924
S.D.	0.039010279550324
T-STAT	2.64534806880325
p-value	0.0159593577711054

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-7.06901156893613
beta	1.84650081435865
S.D.	0.875477095570863
T-STAT	2.10913663384263
p-value	0.0484293263469884
Lambda	-0.846500814358652

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -7.06901156893613 \tabularnewline
beta & 1.84650081435865 \tabularnewline
S.D. & 0.875477095570863 \tabularnewline
T-STAT & 2.10913663384263 \tabularnewline
p-value & 0.0484293263469884 \tabularnewline
Lambda & -0.846500814358652 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=79058&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-7.06901156893613[/C][/ROW]
[ROW][C]beta[/C][C]1.84650081435865[/C][/ROW]
[ROW][C]S.D.[/C][C]0.875477095570863[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.10913663384263[/C][/ROW]
[ROW][C]p-value[/C][C]0.0484293263469884[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.846500814358652[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=79058&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=79058&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	-7.06901156893613
beta	1.84650081435865
S.D.	0.875477095570863
T-STAT	2.10913663384263
p-value	0.0484293263469884
Lambda	-0.846500814358652

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code