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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 12 Dec 2008 04:34:29 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/12/t122908170294hzabet8n4i2b3.htm/, Retrieved Sun, 19 May 2024 04:01:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32573, Retrieved Sun, 19 May 2024 04:01:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact218
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Uitvoer.Nederland] [2008-12-03 15:11:10] [988ab43f527fc78aae41c84649095267]
-   P   [Univariate Data Series] [Export From Belgi...] [2008-12-03 15:52:29] [988ab43f527fc78aae41c84649095267]
- RMP     [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-03 16:25:18] [988ab43f527fc78aae41c84649095267]
-   PD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-11 17:25:17] [988ab43f527fc78aae41c84649095267]
-    D          [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-12 11:34:29] [5d823194959040fa9b19b8c8302177e6] [Current]
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Dataseries X:
3258.1
3140.1
3627.4
3279.4
3204
3515.6
3146.6
2271.7
3627.9
3553.4
3018.3
3355.4
3242
3311.1
4125.2
3423
3120.3
3863
3240.8
2837.4
3945
3684.1
3659.6
3769.6
3592.7
3754
4507.8
3853.2
3817.2
3958.4
3428.9
3125.7
3977
3983.3
4299.6
4306.9
4259.5
3986
4755.6
3925.6
4206.5
4323.4
3816.1
3410.7
4227.4
4296.9
4351.7
3800
4277
4100.2
4672.5
4189.9
4231.9
4654.9
4298.5
3635.9
4505.1
4891.9
4894.2
4093.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32573&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32573&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32573&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13249.825368.7218960014571356.2
23518.425382.2441036467761287.8
33883.725387.7721475416861382.1
44113.28333333333346.6570713998421344.9
54370.43333333333368.2478447343791258.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3249.825 & 368.721896001457 & 1356.2 \tabularnewline
2 & 3518.425 & 382.244103646776 & 1287.8 \tabularnewline
3 & 3883.725 & 387.772147541686 & 1382.1 \tabularnewline
4 & 4113.28333333333 & 346.657071399842 & 1344.9 \tabularnewline
5 & 4370.43333333333 & 368.247844734379 & 1258.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32573&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]3249.825[/C][C]368.721896001457[/C][C]1356.2[/C][/ROW]
[ROW][C]2[/C][C]3518.425[/C][C]382.244103646776[/C][C]1287.8[/C][/ROW]
[ROW][C]3[/C][C]3883.725[/C][C]387.772147541686[/C][C]1382.1[/C][/ROW]
[ROW][C]4[/C][C]4113.28333333333[/C][C]346.657071399842[/C][C]1344.9[/C][/ROW]
[ROW][C]5[/C][C]4370.43333333333[/C][C]368.247844734379[/C][C]1258.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32573&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32573&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
SectionMeanStandard DeviationRange
13249.825368.7218960014571356.2
23518.425382.2441036467761287.8
33883.725387.7721475416861382.1
44113.28333333333346.6570713998421344.9
54370.43333333333368.2478447343791258.3







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha416.472785050794
beta-0.0119525787682004
S.D.0.0192282681104127
T-STAT-0.621614942103276
p-value0.578232578188832

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 416.472785050794 \tabularnewline
beta & -0.0119525787682004 \tabularnewline
S.D. & 0.0192282681104127 \tabularnewline
T-STAT & -0.621614942103276 \tabularnewline
p-value & 0.578232578188832 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32573&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]416.472785050794[/C][/ROW]
[ROW][C]beta[/C][C]-0.0119525787682004[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0192282681104127[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.621614942103276[/C][/ROW]
[ROW][C]p-value[/C][C]0.578232578188832[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32573&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32573&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)
alpha416.472785050794
beta-0.0119525787682004
S.D.0.0192282681104127
T-STAT-0.621614942103276
p-value0.578232578188832







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.90050322073295
beta-0.119571859654066
S.D.0.198843811380525
T-STAT-0.601335585070046
p-value0.590018900108504
Lambda1.11957185965407

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.90050322073295 \tabularnewline
beta & -0.119571859654066 \tabularnewline
S.D. & 0.198843811380525 \tabularnewline
T-STAT & -0.601335585070046 \tabularnewline
p-value & 0.590018900108504 \tabularnewline
Lambda & 1.11957185965407 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32573&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.90050322073295[/C][/ROW]
[ROW][C]beta[/C][C]-0.119571859654066[/C][/ROW]
[ROW][C]S.D.[/C][C]0.198843811380525[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.601335585070046[/C][/ROW]
[ROW][C]p-value[/C][C]0.590018900108504[/C][/ROW]
[ROW][C]Lambda[/C][C]1.11957185965407[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32573&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32573&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)
alpha6.90050322073295
beta-0.119571859654066
S.D.0.198843811380525
T-STAT-0.601335585070046
p-value0.590018900108504
Lambda1.11957185965407



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')