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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 06 Jun 2009 10:39:02 -0600
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/Jun/06/t1244306382bc0zobcz0i8skht.htm/, Retrieved Mon, 29 Apr 2024 04:38:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=42032, Retrieved Mon, 29 Apr 2024 04:38:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [mauro de colfmake...] [2009-06-06 16:39:02] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0.22
0.22
0.2
0.21
0.21
0.19
0.19
0.18
0.18
0.19
0.18
0.17
0.17
0.17
0.18
0.2
0.2
0.2
0.22
0.23
0.25
0.25
0.27
0.29
0.3
0.31
0.33
0.31
0.33
0.33
0.35
0.37
0.47
0.45
0.45
0.4
0.34
0.35
0.34
0.35
0.36
0.37
0.36
0.35
0.36
0.33
0.3
0.28
0.28
0.28
0.3
0.32
0.32
0.3
0.3
0.31
0.33
0.34
0.31
0.33
0.35
0.38
0.4
0.32
0.29
0.3
0.3
0.32
0.32
0.32
0.32
0.32
0.33
0.31
0.33
0.35
0.37
0.37
0.38
0.42
0.42
0.49
0.45
0.41
0.4
0.42
0.47
0.49
0.47
0.52
0.56
0.57
0.61
0.52
0.5
0.5




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=42032&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=42032&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42032&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
10.1950.01678744119329040.05
20.2191666666666670.03941811612428830.12
30.3666666666666670.06095204274797950.17
40.3408333333333330.02644319239884670.09
50.310.01906925178491180.06
60.3283333333333330.03270622218625950.11
70.3858333333333330.05367551216393380.18
80.50250.06001893640571060.21

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.195 & 0.0167874411932904 & 0.05 \tabularnewline
2 & 0.219166666666667 & 0.0394181161242883 & 0.12 \tabularnewline
3 & 0.366666666666667 & 0.0609520427479795 & 0.17 \tabularnewline
4 & 0.340833333333333 & 0.0264431923988467 & 0.09 \tabularnewline
5 & 0.31 & 0.0190692517849118 & 0.06 \tabularnewline
6 & 0.328333333333333 & 0.0327062221862595 & 0.11 \tabularnewline
7 & 0.385833333333333 & 0.0536755121639338 & 0.18 \tabularnewline
8 & 0.5025 & 0.0600189364057106 & 0.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42032&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]0.195[/C][C]0.0167874411932904[/C][C]0.05[/C][/ROW]
[ROW][C]2[/C][C]0.219166666666667[/C][C]0.0394181161242883[/C][C]0.12[/C][/ROW]
[ROW][C]3[/C][C]0.366666666666667[/C][C]0.0609520427479795[/C][C]0.17[/C][/ROW]
[ROW][C]4[/C][C]0.340833333333333[/C][C]0.0264431923988467[/C][C]0.09[/C][/ROW]
[ROW][C]5[/C][C]0.31[/C][C]0.0190692517849118[/C][C]0.06[/C][/ROW]
[ROW][C]6[/C][C]0.328333333333333[/C][C]0.0327062221862595[/C][C]0.11[/C][/ROW]
[ROW][C]7[/C][C]0.385833333333333[/C][C]0.0536755121639338[/C][C]0.18[/C][/ROW]
[ROW][C]8[/C][C]0.5025[/C][C]0.0600189364057106[/C][C]0.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42032&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42032&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
10.1950.01678744119329040.05
20.2191666666666670.03941811612428830.12
30.3666666666666670.06095204274797950.17
40.3408333333333330.02644319239884670.09
50.310.01906925178491180.06
60.3283333333333330.03270622218625950.11
70.3858333333333330.05367551216393380.18
80.50250.06001893640571060.21







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.00438901932326101
beta0.129962065295648
S.D.0.0535910382748616
T-STAT2.42507086033843
p-value0.0515065618778822

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.00438901932326101 \tabularnewline
beta & 0.129962065295648 \tabularnewline
S.D. & 0.0535910382748616 \tabularnewline
T-STAT & 2.42507086033843 \tabularnewline
p-value & 0.0515065618778822 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42032&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.00438901932326101[/C][/ROW]
[ROW][C]beta[/C][C]0.129962065295648[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0535910382748616[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.42507086033843[/C][/ROW]
[ROW][C]p-value[/C][C]0.0515065618778822[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42032&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42032&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-0.00438901932326101
beta0.129962065295648
S.D.0.0535910382748616
T-STAT2.42507086033843
p-value0.0515065618778822







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.09749141860034
beta1.1016785718604
S.D.0.505062591509531
T-STAT2.18127137186641
p-value0.0719351217674321
Lambda-0.101678571860400

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.09749141860034 \tabularnewline
beta & 1.1016785718604 \tabularnewline
S.D. & 0.505062591509531 \tabularnewline
T-STAT & 2.18127137186641 \tabularnewline
p-value & 0.0719351217674321 \tabularnewline
Lambda & -0.101678571860400 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=42032&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.09749141860034[/C][/ROW]
[ROW][C]beta[/C][C]1.1016785718604[/C][/ROW]
[ROW][C]S.D.[/C][C]0.505062591509531[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.18127137186641[/C][/ROW]
[ROW][C]p-value[/C][C]0.0719351217674321[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.101678571860400[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=42032&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=42032&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-2.09749141860034
beta1.1016785718604
S.D.0.505062591509531
T-STAT2.18127137186641
p-value0.0719351217674321
Lambda-0.101678571860400



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')