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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 17 Dec 2009 15:45:18 -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/2009/Dec/17/t1261089948a2cpt3i11moykpi.htm/, Retrieved Tue, 30 Apr 2024 00:08:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69132, Retrieved Tue, 30 Apr 2024 00:08:30 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2009-12-17 22:45:18] [e24e91da8d334fb8882bf413603fde71] [Current]
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Dataseries X:
0.8
1.1
1.3
1.2
1.3
1.1
1.3
1.2
1.6
1.7
1.5
0.9
1.5
1.4
1.6
1.7
1.4
1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2
2.7
2.1
1.9
0.6
0.7
-0.2
-1
-1.7
-0.7




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=69132&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=69132&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69132&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
11.10.2160246899469290.5
21.2250.09574271077563380.2
31.4250.3593976442141300.8
41.550.1290994448735810.3
51.5750.2061552812808830.4
61.5750.6238322424070971.4
71.9750.1258305739211790.3
82.2250.3593976442141310.8
92.450.2380476142847620.5
102.8250.150.3
112.5250.3201562118716420.6
122.60.2828427124746190.6
132.2750.2629955639676580.6
141.8750.2061552812808830.4
151.6750.250.5
161.30.08164965809277260.2
172.9250.5439056290693571.3
184.30.6271629240742261.5
195.650.2380476142847620.5
203.21.157583690279022.7
210.750.8660254037844392.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.1 & 0.216024689946929 & 0.5 \tabularnewline
2 & 1.225 & 0.0957427107756338 & 0.2 \tabularnewline
3 & 1.425 & 0.359397644214130 & 0.8 \tabularnewline
4 & 1.55 & 0.129099444873581 & 0.3 \tabularnewline
5 & 1.575 & 0.206155281280883 & 0.4 \tabularnewline
6 & 1.575 & 0.623832242407097 & 1.4 \tabularnewline
7 & 1.975 & 0.125830573921179 & 0.3 \tabularnewline
8 & 2.225 & 0.359397644214131 & 0.8 \tabularnewline
9 & 2.45 & 0.238047614284762 & 0.5 \tabularnewline
10 & 2.825 & 0.15 & 0.3 \tabularnewline
11 & 2.525 & 0.320156211871642 & 0.6 \tabularnewline
12 & 2.6 & 0.282842712474619 & 0.6 \tabularnewline
13 & 2.275 & 0.262995563967658 & 0.6 \tabularnewline
14 & 1.875 & 0.206155281280883 & 0.4 \tabularnewline
15 & 1.675 & 0.25 & 0.5 \tabularnewline
16 & 1.3 & 0.0816496580927726 & 0.2 \tabularnewline
17 & 2.925 & 0.543905629069357 & 1.3 \tabularnewline
18 & 4.3 & 0.627162924074226 & 1.5 \tabularnewline
19 & 5.65 & 0.238047614284762 & 0.5 \tabularnewline
20 & 3.2 & 1.15758369027902 & 2.7 \tabularnewline
21 & 0.75 & 0.866025403784439 & 2.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69132&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]1.1[/C][C]0.216024689946929[/C][C]0.5[/C][/ROW]
[ROW][C]2[/C][C]1.225[/C][C]0.0957427107756338[/C][C]0.2[/C][/ROW]
[ROW][C]3[/C][C]1.425[/C][C]0.359397644214130[/C][C]0.8[/C][/ROW]
[ROW][C]4[/C][C]1.55[/C][C]0.129099444873581[/C][C]0.3[/C][/ROW]
[ROW][C]5[/C][C]1.575[/C][C]0.206155281280883[/C][C]0.4[/C][/ROW]
[ROW][C]6[/C][C]1.575[/C][C]0.623832242407097[/C][C]1.4[/C][/ROW]
[ROW][C]7[/C][C]1.975[/C][C]0.125830573921179[/C][C]0.3[/C][/ROW]
[ROW][C]8[/C][C]2.225[/C][C]0.359397644214131[/C][C]0.8[/C][/ROW]
[ROW][C]9[/C][C]2.45[/C][C]0.238047614284762[/C][C]0.5[/C][/ROW]
[ROW][C]10[/C][C]2.825[/C][C]0.15[/C][C]0.3[/C][/ROW]
[ROW][C]11[/C][C]2.525[/C][C]0.320156211871642[/C][C]0.6[/C][/ROW]
[ROW][C]12[/C][C]2.6[/C][C]0.282842712474619[/C][C]0.6[/C][/ROW]
[ROW][C]13[/C][C]2.275[/C][C]0.262995563967658[/C][C]0.6[/C][/ROW]
[ROW][C]14[/C][C]1.875[/C][C]0.206155281280883[/C][C]0.4[/C][/ROW]
[ROW][C]15[/C][C]1.675[/C][C]0.25[/C][C]0.5[/C][/ROW]
[ROW][C]16[/C][C]1.3[/C][C]0.0816496580927726[/C][C]0.2[/C][/ROW]
[ROW][C]17[/C][C]2.925[/C][C]0.543905629069357[/C][C]1.3[/C][/ROW]
[ROW][C]18[/C][C]4.3[/C][C]0.627162924074226[/C][C]1.5[/C][/ROW]
[ROW][C]19[/C][C]5.65[/C][C]0.238047614284762[/C][C]0.5[/C][/ROW]
[ROW][C]20[/C][C]3.2[/C][C]1.15758369027902[/C][C]2.7[/C][/ROW]
[ROW][C]21[/C][C]0.75[/C][C]0.866025403784439[/C][C]2.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69132&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69132&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
11.10.2160246899469290.5
21.2250.09574271077563380.2
31.4250.3593976442141300.8
41.550.1290994448735810.3
51.5750.2061552812808830.4
61.5750.6238322424070971.4
71.9750.1258305739211790.3
82.2250.3593976442141310.8
92.450.2380476142847620.5
102.8250.150.3
112.5250.3201562118716420.6
122.60.2828427124746190.6
132.2750.2629955639676580.6
141.8750.2061552812808830.4
151.6750.250.5
161.30.08164965809277260.2
172.9250.5439056290693571.3
184.30.6271629240742261.5
195.650.2380476142847620.5
203.21.157583690279022.7
210.750.8660254037844392.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.259298487501765
beta0.0403145595225670
S.D.0.0543266435936112
T-STAT0.742077125620695
p-value0.467115847823731

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.259298487501765 \tabularnewline
beta & 0.0403145595225670 \tabularnewline
S.D. & 0.0543266435936112 \tabularnewline
T-STAT & 0.742077125620695 \tabularnewline
p-value & 0.467115847823731 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69132&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.259298487501765[/C][/ROW]
[ROW][C]beta[/C][C]0.0403145595225670[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0543266435936112[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.742077125620695[/C][/ROW]
[ROW][C]p-value[/C][C]0.467115847823731[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69132&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69132&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)
alpha0.259298487501765
beta0.0403145595225670
S.D.0.0543266435936112
T-STAT0.742077125620695
p-value0.467115847823731







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.50184330723471
beta0.299633445234272
S.D.0.334421797827527
T-STAT0.895974625998522
p-value0.381477975629903
Lambda0.700366554765728

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.50184330723471 \tabularnewline
beta & 0.299633445234272 \tabularnewline
S.D. & 0.334421797827527 \tabularnewline
T-STAT & 0.895974625998522 \tabularnewline
p-value & 0.381477975629903 \tabularnewline
Lambda & 0.700366554765728 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69132&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.50184330723471[/C][/ROW]
[ROW][C]beta[/C][C]0.299633445234272[/C][/ROW]
[ROW][C]S.D.[/C][C]0.334421797827527[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.895974625998522[/C][/ROW]
[ROW][C]p-value[/C][C]0.381477975629903[/C][/ROW]
[ROW][C]Lambda[/C][C]0.700366554765728[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69132&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69132&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-1.50184330723471
beta0.299633445234272
S.D.0.334421797827527
T-STAT0.895974625998522
p-value0.381477975629903
Lambda0.700366554765728



Parameters (Session):
par1 = 12 ; par2 = 0.0 ; par3 = 2 ; par4 = 0 ; par5 = 1 ; par6 = 2 ; par7 = 0 ; par8 = 0 ; par9 = 1 ; par10 = FALSE ;
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')