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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, 12 May 2008 02:11:26 -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/12/t1210579936amldrzz08s6ci32.htm/, Retrieved Tue, 14 May 2024 14:12:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12304, Retrieved Tue, 14 May 2024 14:12:58 +0000

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Original text written by user:

bron: belgostat

IsPrivate?

No (this computation is public)

User-defined keywords

periode: januari 2000 tot en met januari 2008

Estimated Impact

210

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

-       [Standard Deviation-Mean Plot] [Laurane Poti� -Go...] [2008-05-12 08:11:26] [8c9b3412c86ca5b785d4e204c3e8d338] [Current]

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Boxplots

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	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12304&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12304&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12304&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	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	9459.75	317.259488957121	761
2	9707.5	47.3462423711393	106
3	9980.75	177.263222355908	405
4	9240	134.578353881051	291
5	9963.75	185.080838194197	449
6	10010.75	42.5626988492663	103
7	10706.25	323.071070612438	704
8	10544	430.637511913055	831
9	10395	116.661904664719	267
10	10360.5	513.559149465765	1091
11	10005	247.325696198353	543
12	10657.5	180.725390210304	433
13	10593.5	236.466347147609	575
14	10421	116.301332752467	278
15	10738.75	118.935206450123	247
16	10518	105.157025442906	239
17	11213	344.022286099801	749
18	12845.25	778.735460003374	1848
19	15091.5	633.042652591435	1461
20	16030.25	785.086141770443	1896
21	15261	295.144032634915	694
22	16006.5	332.966965328394	769
23	15731.75	145.866091558891	343
24	17227.75	618.823817145613	1307

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 9459.75 & 317.259488957121 & 761 \tabularnewline
2 & 9707.5 & 47.3462423711393 & 106 \tabularnewline
3 & 9980.75 & 177.263222355908 & 405 \tabularnewline
4 & 9240 & 134.578353881051 & 291 \tabularnewline
5 & 9963.75 & 185.080838194197 & 449 \tabularnewline
6 & 10010.75 & 42.5626988492663 & 103 \tabularnewline
7 & 10706.25 & 323.071070612438 & 704 \tabularnewline
8 & 10544 & 430.637511913055 & 831 \tabularnewline
9 & 10395 & 116.661904664719 & 267 \tabularnewline
10 & 10360.5 & 513.559149465765 & 1091 \tabularnewline
11 & 10005 & 247.325696198353 & 543 \tabularnewline
12 & 10657.5 & 180.725390210304 & 433 \tabularnewline
13 & 10593.5 & 236.466347147609 & 575 \tabularnewline
14 & 10421 & 116.301332752467 & 278 \tabularnewline
15 & 10738.75 & 118.935206450123 & 247 \tabularnewline
16 & 10518 & 105.157025442906 & 239 \tabularnewline
17 & 11213 & 344.022286099801 & 749 \tabularnewline
18 & 12845.25 & 778.735460003374 & 1848 \tabularnewline
19 & 15091.5 & 633.042652591435 & 1461 \tabularnewline
20 & 16030.25 & 785.086141770443 & 1896 \tabularnewline
21 & 15261 & 295.144032634915 & 694 \tabularnewline
22 & 16006.5 & 332.966965328394 & 769 \tabularnewline
23 & 15731.75 & 145.866091558891 & 343 \tabularnewline
24 & 17227.75 & 618.823817145613 & 1307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12304&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]9459.75[/C][C]317.259488957121[/C][C]761[/C][/ROW]
[ROW][C]2[/C][C]9707.5[/C][C]47.3462423711393[/C][C]106[/C][/ROW]
[ROW][C]3[/C][C]9980.75[/C][C]177.263222355908[/C][C]405[/C][/ROW]
[ROW][C]4[/C][C]9240[/C][C]134.578353881051[/C][C]291[/C][/ROW]
[ROW][C]5[/C][C]9963.75[/C][C]185.080838194197[/C][C]449[/C][/ROW]
[ROW][C]6[/C][C]10010.75[/C][C]42.5626988492663[/C][C]103[/C][/ROW]
[ROW][C]7[/C][C]10706.25[/C][C]323.071070612438[/C][C]704[/C][/ROW]
[ROW][C]8[/C][C]10544[/C][C]430.637511913055[/C][C]831[/C][/ROW]
[ROW][C]9[/C][C]10395[/C][C]116.661904664719[/C][C]267[/C][/ROW]
[ROW][C]10[/C][C]10360.5[/C][C]513.559149465765[/C][C]1091[/C][/ROW]
[ROW][C]11[/C][C]10005[/C][C]247.325696198353[/C][C]543[/C][/ROW]
[ROW][C]12[/C][C]10657.5[/C][C]180.725390210304[/C][C]433[/C][/ROW]
[ROW][C]13[/C][C]10593.5[/C][C]236.466347147609[/C][C]575[/C][/ROW]
[ROW][C]14[/C][C]10421[/C][C]116.301332752467[/C][C]278[/C][/ROW]
[ROW][C]15[/C][C]10738.75[/C][C]118.935206450123[/C][C]247[/C][/ROW]
[ROW][C]16[/C][C]10518[/C][C]105.157025442906[/C][C]239[/C][/ROW]
[ROW][C]17[/C][C]11213[/C][C]344.022286099801[/C][C]749[/C][/ROW]
[ROW][C]18[/C][C]12845.25[/C][C]778.735460003374[/C][C]1848[/C][/ROW]
[ROW][C]19[/C][C]15091.5[/C][C]633.042652591435[/C][C]1461[/C][/ROW]
[ROW][C]20[/C][C]16030.25[/C][C]785.086141770443[/C][C]1896[/C][/ROW]
[ROW][C]21[/C][C]15261[/C][C]295.144032634915[/C][C]694[/C][/ROW]
[ROW][C]22[/C][C]16006.5[/C][C]332.966965328394[/C][C]769[/C][/ROW]
[ROW][C]23[/C][C]15731.75[/C][C]145.866091558891[/C][C]343[/C][/ROW]
[ROW][C]24[/C][C]17227.75[/C][C]618.823817145613[/C][C]1307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12304&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12304&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	9459.75	317.259488957121	761
2	9707.5	47.3462423711393	106
3	9980.75	177.263222355908	405
4	9240	134.578353881051	291
5	9963.75	185.080838194197	449
6	10010.75	42.5626988492663	103
7	10706.25	323.071070612438	704
8	10544	430.637511913055	831
9	10395	116.661904664719	267
10	10360.5	513.559149465765	1091
11	10005	247.325696198353	543
12	10657.5	180.725390210304	433
13	10593.5	236.466347147609	575
14	10421	116.301332752467	278
15	10738.75	118.935206450123	247
16	10518	105.157025442906	239
17	11213	344.022286099801	749
18	12845.25	778.735460003374	1848
19	15091.5	633.042652591435	1461
20	16030.25	785.086141770443	1896
21	15261	295.144032634915	694
22	16006.5	332.966965328394	769
23	15731.75	145.866091558891	343
24	17227.75	618.823817145613	1307

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-288.998866793521
beta	0.0500960058917254
S.D.	0.0150444981172651
T-STAT	3.3298555725322
p-value	0.00303883574034761

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -288.998866793521 \tabularnewline
beta & 0.0500960058917254 \tabularnewline
S.D. & 0.0150444981172651 \tabularnewline
T-STAT & 3.3298555725322 \tabularnewline
p-value & 0.00303883574034761 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12304&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-288.998866793521[/C][/ROW]
[ROW][C]beta[/C][C]0.0500960058917254[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0150444981172651[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.3298555725322[/C][/ROW]
[ROW][C]p-value[/C][C]0.00303883574034761[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12304&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12304&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	-288.998866793521
beta	0.0500960058917254
S.D.	0.0150444981172651
T-STAT	3.3298555725322
p-value	0.00303883574034761

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-14.8822679750706
beta	2.17182858747424
S.D.	0.717730503006687
T-STAT	3.02596668021787
p-value	0.00620903525479209
Lambda	-1.17182858747424

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -14.8822679750706 \tabularnewline
beta & 2.17182858747424 \tabularnewline
S.D. & 0.717730503006687 \tabularnewline
T-STAT & 3.02596668021787 \tabularnewline
p-value & 0.00620903525479209 \tabularnewline
Lambda & -1.17182858747424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12304&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-14.8822679750706[/C][/ROW]
[ROW][C]beta[/C][C]2.17182858747424[/C][/ROW]
[ROW][C]S.D.[/C][C]0.717730503006687[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.02596668021787[/C][/ROW]
[ROW][C]p-value[/C][C]0.00620903525479209[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.17182858747424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12304&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12304&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	-14.8822679750706
beta	2.17182858747424
S.D.	0.717730503006687
T-STAT	3.02596668021787
p-value	0.00620903525479209
Lambda	-1.17182858747424

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