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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, 26 May 2008 17:32:58 -0600

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/2008/May/27/t1211844802t3xj1e8b7ypzgh7.htm/, Retrieved Sun, 19 May 2024 23:03:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13313, Retrieved Sun, 19 May 2024 23:03:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Spreidings en gemiddelde grafieken goudkoers

Estimated Impact

194

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

-       [Standard Deviation-Mean Plot] [Spreidings en gem...] [2008-05-26 23:32:58] [f38aed22bcf737d6f431a6f90e40d4b2] [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=13313&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=13313&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13313&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	10706.25	323.071070612438	704
2	10544	430.637511913055	831
3	10395	116.661904664719	267
4	10360.5	513.559149465765	1091
5	10005	247.325696198353	543
6	10657.5	180.725390210304	433
7	10593.5	236.466347147609	575
8	10421	116.301332752467	278
9	10738.75	118.935206450123	247
10	10518	105.157025442906	239
11	11213	344.022286099801	749
12	12845.25	778.735460003374	1848
13	15091.5	633.042652591435	1461
14	16030.25	785.086141770443	1896
15	15261	295.144032634915	694
16	16006.5	332.966965328394	769
17	15731.75	145.866091558891	343
18	17227.75	618.823817145613	1307

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 10706.25 & 323.071070612438 & 704 \tabularnewline
2 & 10544 & 430.637511913055 & 831 \tabularnewline
3 & 10395 & 116.661904664719 & 267 \tabularnewline
4 & 10360.5 & 513.559149465765 & 1091 \tabularnewline
5 & 10005 & 247.325696198353 & 543 \tabularnewline
6 & 10657.5 & 180.725390210304 & 433 \tabularnewline
7 & 10593.5 & 236.466347147609 & 575 \tabularnewline
8 & 10421 & 116.301332752467 & 278 \tabularnewline
9 & 10738.75 & 118.935206450123 & 247 \tabularnewline
10 & 10518 & 105.157025442906 & 239 \tabularnewline
11 & 11213 & 344.022286099801 & 749 \tabularnewline
12 & 12845.25 & 778.735460003374 & 1848 \tabularnewline
13 & 15091.5 & 633.042652591435 & 1461 \tabularnewline
14 & 16030.25 & 785.086141770443 & 1896 \tabularnewline
15 & 15261 & 295.144032634915 & 694 \tabularnewline
16 & 16006.5 & 332.966965328394 & 769 \tabularnewline
17 & 15731.75 & 145.866091558891 & 343 \tabularnewline
18 & 17227.75 & 618.823817145613 & 1307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13313&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]10706.25[/C][C]323.071070612438[/C][C]704[/C][/ROW]
[ROW][C]2[/C][C]10544[/C][C]430.637511913055[/C][C]831[/C][/ROW]
[ROW][C]3[/C][C]10395[/C][C]116.661904664719[/C][C]267[/C][/ROW]
[ROW][C]4[/C][C]10360.5[/C][C]513.559149465765[/C][C]1091[/C][/ROW]
[ROW][C]5[/C][C]10005[/C][C]247.325696198353[/C][C]543[/C][/ROW]
[ROW][C]6[/C][C]10657.5[/C][C]180.725390210304[/C][C]433[/C][/ROW]
[ROW][C]7[/C][C]10593.5[/C][C]236.466347147609[/C][C]575[/C][/ROW]
[ROW][C]8[/C][C]10421[/C][C]116.301332752467[/C][C]278[/C][/ROW]
[ROW][C]9[/C][C]10738.75[/C][C]118.935206450123[/C][C]247[/C][/ROW]
[ROW][C]10[/C][C]10518[/C][C]105.157025442906[/C][C]239[/C][/ROW]
[ROW][C]11[/C][C]11213[/C][C]344.022286099801[/C][C]749[/C][/ROW]
[ROW][C]12[/C][C]12845.25[/C][C]778.735460003374[/C][C]1848[/C][/ROW]
[ROW][C]13[/C][C]15091.5[/C][C]633.042652591435[/C][C]1461[/C][/ROW]
[ROW][C]14[/C][C]16030.25[/C][C]785.086141770443[/C][C]1896[/C][/ROW]
[ROW][C]15[/C][C]15261[/C][C]295.144032634915[/C][C]694[/C][/ROW]
[ROW][C]16[/C][C]16006.5[/C][C]332.966965328394[/C][C]769[/C][/ROW]
[ROW][C]17[/C][C]15731.75[/C][C]145.866091558891[/C][C]343[/C][/ROW]
[ROW][C]18[/C][C]17227.75[/C][C]618.823817145613[/C][C]1307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13313&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13313&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	10706.25	323.071070612438	704
2	10544	430.637511913055	831
3	10395	116.661904664719	267
4	10360.5	513.559149465765	1091
5	10005	247.325696198353	543
6	10657.5	180.725390210304	433
7	10593.5	236.466347147609	575
8	10421	116.301332752467	278
9	10738.75	118.935206450123	247
10	10518	105.157025442906	239
11	11213	344.022286099801	749
12	12845.25	778.735460003374	1848
13	15091.5	633.042652591435	1461
14	16030.25	785.086141770443	1896
15	15261	295.144032634915	694
16	16006.5	332.966965328394	769
17	15731.75	145.866091558891	343
18	17227.75	618.823817145613	1307

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-196.180141360712
beta	0.0439221054328168
S.D.	0.0189741864551764
T-STAT	2.31483471170561
p-value	0.0342314634951633

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -196.180141360712 \tabularnewline
beta & 0.0439221054328168 \tabularnewline
S.D. & 0.0189741864551764 \tabularnewline
T-STAT & 2.31483471170561 \tabularnewline
p-value & 0.0342314634951633 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13313&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-196.180141360712[/C][/ROW]
[ROW][C]beta[/C][C]0.0439221054328168[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0189741864551764[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.31483471170561[/C][/ROW]
[ROW][C]p-value[/C][C]0.0342314634951633[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13313&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13313&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	-196.180141360712
beta	0.0439221054328168
S.D.	0.0189741864551764
T-STAT	2.31483471170561
p-value	0.0342314634951633

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-10.0702908611668
beta	1.67051595795585
S.D.	0.753596368404172
T-STAT	2.21672506396675
p-value	0.0414773939180424
Lambda	-0.670515957955852

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.0702908611668 \tabularnewline
beta & 1.67051595795585 \tabularnewline
S.D. & 0.753596368404172 \tabularnewline
T-STAT & 2.21672506396675 \tabularnewline
p-value & 0.0414773939180424 \tabularnewline
Lambda & -0.670515957955852 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13313&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.0702908611668[/C][/ROW]
[ROW][C]beta[/C][C]1.67051595795585[/C][/ROW]
[ROW][C]S.D.[/C][C]0.753596368404172[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.21672506396675[/C][/ROW]
[ROW][C]p-value[/C][C]0.0414773939180424[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.670515957955852[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13313&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13313&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	-10.0702908611668
beta	1.67051595795585
S.D.	0.753596368404172
T-STAT	2.21672506396675
p-value	0.0414773939180424
Lambda	-0.670515957955852

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code