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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 13 Dec 2012 13:44:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/13/t1355424293m5q52fwy74njtii.htm/, Retrieved Mon, 29 Apr 2024 03:27:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199357, Retrieved Mon, 29 Apr 2024 03:27:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2012-12-13 18:44:36] [de59db95ac8fc769a5d40184c39d6048] [Current]
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Dataseries X:
227.81
227.81
227.01
227.26
227.1
227.59
227.59
227.7
227.75
226.33
225.95
226.33
226.33
226.22
224.84
221.88
222.37
221.8
221.8
221.8
221.9
220.2
219.95
220.05
220.05
220.05
220.62
221.53
221.61
221.5
221.5
221.87
222.27
220.86
221.49
221.67
221.67
221.72
221.67
220.29
220.75
219.59
219.59
219.59
219.82
221.59
220.9
221.01
221.01
219.69
221
219.82
218.04
217.97
217.97
217.53
217
217.18
217.68
217.71
217.71
218.5
218.8
218.94
220
219.89
219.89
220.08
220.16
221
222.16
221.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199357&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199357&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199357&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 time3 seconds
R Server'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1227.1858333333330.6553619171299481.86000000000001
2222.4283333333332.214570893519616.38000000000002
3221.2516666666670.7019949926437982.22
4220.68250.8784296422387122.13
5218.551.435960242549154.00999999999999
6219.8858333333331.274686830225964.44999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 227.185833333333 & 0.655361917129948 & 1.86000000000001 \tabularnewline
2 & 222.428333333333 & 2.21457089351961 & 6.38000000000002 \tabularnewline
3 & 221.251666666667 & 0.701994992643798 & 2.22 \tabularnewline
4 & 220.6825 & 0.878429642238712 & 2.13 \tabularnewline
5 & 218.55 & 1.43596024254915 & 4.00999999999999 \tabularnewline
6 & 219.885833333333 & 1.27468683022596 & 4.44999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199357&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]227.185833333333[/C][C]0.655361917129948[/C][C]1.86000000000001[/C][/ROW]
[ROW][C]2[/C][C]222.428333333333[/C][C]2.21457089351961[/C][C]6.38000000000002[/C][/ROW]
[ROW][C]3[/C][C]221.251666666667[/C][C]0.701994992643798[/C][C]2.22[/C][/ROW]
[ROW][C]4[/C][C]220.6825[/C][C]0.878429642238712[/C][C]2.13[/C][/ROW]
[ROW][C]5[/C][C]218.55[/C][C]1.43596024254915[/C][C]4.00999999999999[/C][/ROW]
[ROW][C]6[/C][C]219.885833333333[/C][C]1.27468683022596[/C][C]4.44999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199357&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199357&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
1227.1858333333330.6553619171299481.86000000000001
2222.4283333333332.214570893519616.38000000000002
3221.2516666666670.7019949926437982.22
4220.68250.8784296422387122.13
5218.551.435960242549154.00999999999999
6219.8858333333331.274686830225964.44999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha13.87618819098
beta-0.0572158124395514
S.D.0.0939415097484762
T-STAT-0.609057833887744
p-value0.575381554955186

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 13.87618819098 \tabularnewline
beta & -0.0572158124395514 \tabularnewline
S.D. & 0.0939415097484762 \tabularnewline
T-STAT & -0.609057833887744 \tabularnewline
p-value & 0.575381554955186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199357&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]13.87618819098[/C][/ROW]
[ROW][C]beta[/C][C]-0.0572158124395514[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0939415097484762[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.609057833887744[/C][/ROW]
[ROW][C]p-value[/C][C]0.575381554955186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199357&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199357&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)
alpha13.87618819098
beta-0.0572158124395514
S.D.0.0939415097484762
T-STAT-0.609057833887744
p-value0.575381554955186







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha80.392895832139
beta-14.869346115958
S.D.15.7787519997915
T-STAT-0.942365157659769
p-value0.399363244304527
Lambda15.869346115958

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 80.392895832139 \tabularnewline
beta & -14.869346115958 \tabularnewline
S.D. & 15.7787519997915 \tabularnewline
T-STAT & -0.942365157659769 \tabularnewline
p-value & 0.399363244304527 \tabularnewline
Lambda & 15.869346115958 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199357&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]80.392895832139[/C][/ROW]
[ROW][C]beta[/C][C]-14.869346115958[/C][/ROW]
[ROW][C]S.D.[/C][C]15.7787519997915[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.942365157659769[/C][/ROW]
[ROW][C]p-value[/C][C]0.399363244304527[/C][/ROW]
[ROW][C]Lambda[/C][C]15.869346115958[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199357&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199357&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)
alpha80.392895832139
beta-14.869346115958
S.D.15.7787519997915
T-STAT-0.942365157659769
p-value0.399363244304527
Lambda15.869346115958



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')