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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 21 Dec 2009 08:51:38 -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/21/t1261410755v3fk8zfah3onq3a.htm/, Retrieved Sun, 05 May 2024 12:56:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70297, Retrieved Sun, 05 May 2024 12:56:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [] [2009-12-21 15:37:35] [e5e09c53da17fb7444fa9ceb236a5291]
-    D    [Standard Deviation-Mean Plot] [] [2009-12-21 15:51:38] [ab2b68d5442f7c9b7e2e9d790849a234] [Current]
-   P       [Standard Deviation-Mean Plot] [] [2010-01-12 09:03:27] [74be16979710d4c4e7c6647856088456]
- RMPD      [Classical Decomposition] [] [2010-01-12 09:15:15] [e5e09c53da17fb7444fa9ceb236a5291]
-    D        [Classical Decomposition] [] [2010-01-16 10:43:37] [74be16979710d4c4e7c6647856088456]
- RMPD        [Exponential Smoothing] [] [2010-01-16 11:07:46] [74be16979710d4c4e7c6647856088456]
-   PD          [Exponential Smoothing] [] [2010-01-16 11:41:42] [74be16979710d4c4e7c6647856088456]
- RMPD      [Classical Decomposition] [] [2010-01-12 09:35:07] [e5e09c53da17fb7444fa9ceb236a5291]
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Dataseries X:
2.14
2.45
2.52
2.3
2.25
2.06
1.99
2.25
2.26
2.36
2.3
2.19
2.31
2.21
2.21
2.26
2.18
2.21
2.33
2.12
2.08
1.97
2.09
2.11
2.24
2.45
2.68
2.73
2.76
2.83
3.16
3.22
3.22
3.34
3.35
3.42
3.58
3.71
3.68
3.83
3.94
3.88
4.03
4.15
4.32
4.4
4.37
4.14
4.11
4.16
3.98
4.13
3.76
3.66
3.85
4.03
4.31
4.58
4.46
4.41
3.84
2.84
2.66
2.17
1.43
1.47
1.29
1.23
1.09
0.94
0.76
0.67




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=70297&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=70297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70297&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
12.35250.1687947471536560.38
22.13750.1330100246848580.26
32.27750.07135591542869210.17
42.24750.04787135538781690.1
52.210.08831760866327850.21
62.06250.06291528696058960.14
72.5250.2257579825092940.49
82.99250.2311384866265250.46
93.33250.08301606270274840.200000000000000
103.70.102956301409870.25
1140.1174734012447080.270000000000000
124.30750.1164402564980570.260000000000001
134.0950.07937253933193780.18
143.8250.1571623364550170.37
154.440.1122497216032180.270000000000000
162.87750.7013498889047221.67
171.3550.1135781669160050.24
180.8650.1873499399519520.42

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.3525 & 0.168794747153656 & 0.38 \tabularnewline
2 & 2.1375 & 0.133010024684858 & 0.26 \tabularnewline
3 & 2.2775 & 0.0713559154286921 & 0.17 \tabularnewline
4 & 2.2475 & 0.0478713553878169 & 0.1 \tabularnewline
5 & 2.21 & 0.0883176086632785 & 0.21 \tabularnewline
6 & 2.0625 & 0.0629152869605896 & 0.14 \tabularnewline
7 & 2.525 & 0.225757982509294 & 0.49 \tabularnewline
8 & 2.9925 & 0.231138486626525 & 0.46 \tabularnewline
9 & 3.3325 & 0.0830160627027484 & 0.200000000000000 \tabularnewline
10 & 3.7 & 0.10295630140987 & 0.25 \tabularnewline
11 & 4 & 0.117473401244708 & 0.270000000000000 \tabularnewline
12 & 4.3075 & 0.116440256498057 & 0.260000000000001 \tabularnewline
13 & 4.095 & 0.0793725393319378 & 0.18 \tabularnewline
14 & 3.825 & 0.157162336455017 & 0.37 \tabularnewline
15 & 4.44 & 0.112249721603218 & 0.270000000000000 \tabularnewline
16 & 2.8775 & 0.701349888904722 & 1.67 \tabularnewline
17 & 1.355 & 0.113578166916005 & 0.24 \tabularnewline
18 & 0.865 & 0.187349939951952 & 0.42 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70297&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]2.3525[/C][C]0.168794747153656[/C][C]0.38[/C][/ROW]
[ROW][C]2[/C][C]2.1375[/C][C]0.133010024684858[/C][C]0.26[/C][/ROW]
[ROW][C]3[/C][C]2.2775[/C][C]0.0713559154286921[/C][C]0.17[/C][/ROW]
[ROW][C]4[/C][C]2.2475[/C][C]0.0478713553878169[/C][C]0.1[/C][/ROW]
[ROW][C]5[/C][C]2.21[/C][C]0.0883176086632785[/C][C]0.21[/C][/ROW]
[ROW][C]6[/C][C]2.0625[/C][C]0.0629152869605896[/C][C]0.14[/C][/ROW]
[ROW][C]7[/C][C]2.525[/C][C]0.225757982509294[/C][C]0.49[/C][/ROW]
[ROW][C]8[/C][C]2.9925[/C][C]0.231138486626525[/C][C]0.46[/C][/ROW]
[ROW][C]9[/C][C]3.3325[/C][C]0.0830160627027484[/C][C]0.200000000000000[/C][/ROW]
[ROW][C]10[/C][C]3.7[/C][C]0.10295630140987[/C][C]0.25[/C][/ROW]
[ROW][C]11[/C][C]4[/C][C]0.117473401244708[/C][C]0.270000000000000[/C][/ROW]
[ROW][C]12[/C][C]4.3075[/C][C]0.116440256498057[/C][C]0.260000000000001[/C][/ROW]
[ROW][C]13[/C][C]4.095[/C][C]0.0793725393319378[/C][C]0.18[/C][/ROW]
[ROW][C]14[/C][C]3.825[/C][C]0.157162336455017[/C][C]0.37[/C][/ROW]
[ROW][C]15[/C][C]4.44[/C][C]0.112249721603218[/C][C]0.270000000000000[/C][/ROW]
[ROW][C]16[/C][C]2.8775[/C][C]0.701349888904722[/C][C]1.67[/C][/ROW]
[ROW][C]17[/C][C]1.355[/C][C]0.113578166916005[/C][C]0.24[/C][/ROW]
[ROW][C]18[/C][C]0.865[/C][C]0.187349939951952[/C][C]0.42[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70297&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
12.35250.1687947471536560.38
22.13750.1330100246848580.26
32.27750.07135591542869210.17
42.24750.04787135538781690.1
52.210.08831760866327850.21
62.06250.06291528696058960.14
72.5250.2257579825092940.49
82.99250.2311384866265250.46
93.33250.08301606270274840.200000000000000
103.70.102956301409870.25
1140.1174734012447080.270000000000000
124.30750.1164402564980570.260000000000001
134.0950.07937253933193780.18
143.8250.1571623364550170.37
154.440.1122497216032180.270000000000000
162.87750.7013498889047221.67
171.3550.1135781669160050.24
180.8650.1873499399519520.42







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.171546304794913
beta-0.00557576597791742
S.D.0.0352500424854487
T-STAT-0.158177567593546
p-value0.876296041203469

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.171546304794913 \tabularnewline
beta & -0.00557576597791742 \tabularnewline
S.D. & 0.0352500424854487 \tabularnewline
T-STAT & -0.158177567593546 \tabularnewline
p-value & 0.876296041203469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70297&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.171546304794913[/C][/ROW]
[ROW][C]beta[/C][C]-0.00557576597791742[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0352500424854487[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.158177567593546[/C][/ROW]
[ROW][C]p-value[/C][C]0.876296041203469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70297&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70297&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)
alpha0.171546304794913
beta-0.00557576597791742
S.D.0.0352500424854487
T-STAT-0.158177567593546
p-value0.876296041203469







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.03031711422846
beta-0.0514557240627455
S.D.0.356004404297386
T-STAT-0.144536762583876
p-value0.88688158992004
Lambda1.05145572406275

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.03031711422846 \tabularnewline
beta & -0.0514557240627455 \tabularnewline
S.D. & 0.356004404297386 \tabularnewline
T-STAT & -0.144536762583876 \tabularnewline
p-value & 0.88688158992004 \tabularnewline
Lambda & 1.05145572406275 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70297&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.03031711422846[/C][/ROW]
[ROW][C]beta[/C][C]-0.0514557240627455[/C][/ROW]
[ROW][C]S.D.[/C][C]0.356004404297386[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.144536762583876[/C][/ROW]
[ROW][C]p-value[/C][C]0.88688158992004[/C][/ROW]
[ROW][C]Lambda[/C][C]1.05145572406275[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70297&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70297&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-2.03031711422846
beta-0.0514557240627455
S.D.0.356004404297386
T-STAT-0.144536762583876
p-value0.88688158992004
Lambda1.05145572406275



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')