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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 18 Mar 2016 15:51:23 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Mar/18/t1458316417egka5j5cq7mjkrt.htm/, Retrieved Thu, 02 May 2024 05:51:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294280, Retrieved Thu, 02 May 2024 05:51:18 +0000
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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] [] [2016-03-18 15:51:23] [409a9d71664281dd1fd3bb0995266dd0] [Current]
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Dataseries X:
100.57
100.27
100.27
100.18
100.16
100.18
100.18
100.59
100.69
101.06
101.15
101.16
101.16
100.81
100.94
101.13
101.29
101.34
101.35
101.7
102.05
102.48
102.66
102.72
102.73
102.18
102.22
102.37
102.53
102.61
102.62
103
103.17
103.52
103.69
103.73
99.57
99.09
99.14
99.36
99.6
99.65
99.8
100.15
100.45
100.89
101.13
101.17
101.21
101.1
101.17
101.11
101.2
101.15
100.92
101.1
101.22
101.25
101.39
101.43
101.95
101.92
102.05
102.07
102.1
102.16
101.63
101.43
101.4
101.6
101.72
101.73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 1 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294280&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294280&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294280&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'Sir Maurice George Kendall' @ kendall.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.5383333333330.396778695664641
2101.6358333333330.6775552085299471.91
3102.8641666666670.5522591343881511.55
41000.7475779071593322.08
5101.18750.1348483997275880.510000000000005
6101.8133333333330.2640362693175880.759999999999991

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.538333333333 & 0.39677869566464 & 1 \tabularnewline
2 & 101.635833333333 & 0.677555208529947 & 1.91 \tabularnewline
3 & 102.864166666667 & 0.552259134388151 & 1.55 \tabularnewline
4 & 100 & 0.747577907159332 & 2.08 \tabularnewline
5 & 101.1875 & 0.134848399727588 & 0.510000000000005 \tabularnewline
6 & 101.813333333333 & 0.264036269317588 & 0.759999999999991 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294280&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]100.538333333333[/C][C]0.39677869566464[/C][C]1[/C][/ROW]
[ROW][C]2[/C][C]101.635833333333[/C][C]0.677555208529947[/C][C]1.91[/C][/ROW]
[ROW][C]3[/C][C]102.864166666667[/C][C]0.552259134388151[/C][C]1.55[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]0.747577907159332[/C][C]2.08[/C][/ROW]
[ROW][C]5[/C][C]101.1875[/C][C]0.134848399727588[/C][C]0.510000000000005[/C][/ROW]
[ROW][C]6[/C][C]101.813333333333[/C][C]0.264036269317588[/C][C]0.759999999999991[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294280&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294280&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
1100.5383333333330.396778695664641
2101.6358333333330.6775552085299471.91
3102.8641666666670.5522591343881511.55
41000.7475779071593322.08
5101.18750.1348483997275880.510000000000005
6101.8133333333330.2640362693175880.759999999999991







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.89962805487781
beta-0.0339200397690603
S.D.0.117361595579671
T-STAT-0.289021630981779
p-value0.786925211033391

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.89962805487781 \tabularnewline
beta & -0.0339200397690603 \tabularnewline
S.D. & 0.117361595579671 \tabularnewline
T-STAT & -0.289021630981779 \tabularnewline
p-value & 0.786925211033391 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294280&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.89962805487781[/C][/ROW]
[ROW][C]beta[/C][C]-0.0339200397690603[/C][/ROW]
[ROW][C]S.D.[/C][C]0.117361595579671[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.289021630981779[/C][/ROW]
[ROW][C]p-value[/C][C]0.786925211033391[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294280&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294280&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)
alpha3.89962805487781
beta-0.0339200397690603
S.D.0.117361595579671
T-STAT-0.289021630981779
p-value0.786925211033391







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha19.6588453365615
beta-4.45629116299956
S.D.32.6847333643969
T-STAT-0.136341670997192
p-value0.898137833682753
Lambda5.45629116299956

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 19.6588453365615 \tabularnewline
beta & -4.45629116299956 \tabularnewline
S.D. & 32.6847333643969 \tabularnewline
T-STAT & -0.136341670997192 \tabularnewline
p-value & 0.898137833682753 \tabularnewline
Lambda & 5.45629116299956 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294280&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]19.6588453365615[/C][/ROW]
[ROW][C]beta[/C][C]-4.45629116299956[/C][/ROW]
[ROW][C]S.D.[/C][C]32.6847333643969[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.136341670997192[/C][/ROW]
[ROW][C]p-value[/C][C]0.898137833682753[/C][/ROW]
[ROW][C]Lambda[/C][C]5.45629116299956[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294280&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294280&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)
alpha19.6588453365615
beta-4.45629116299956
S.D.32.6847333643969
T-STAT-0.136341670997192
p-value0.898137833682753
Lambda5.45629116299956



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')