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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 28 Apr 2014 16:24:08 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Apr/28/t1398716659cys8tsinhgx17ws.htm/, Retrieved Fri, 17 May 2024 03:05:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=234721, Retrieved Fri, 17 May 2024 03:05:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact64
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2014-04-28 20:24:08] [0f40cba20c222b7b9166042309a72bac] [Current]
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Dataseries X:
55.64
56.13
56.69
56.8
56.93
57
57.01
57.21
57.17
57.36
57.29
57.26
57.29
57.68
58.19
58.34
58.46
58.67
58.72
58.74
58.77
58.84
59.13
59.12
59.12
59.33
59.49
59.67
59.7
59.73
59.74
59.62
59.6
59.98
60.05
60.06
60.1
60.18
60.38
60.52
60.78
60.72
60.72
60.86
60.99
61.11
61.17
61.19
61.19
61.22
61.19
60.82
60.6
60.15
60.14
60.2
60.36
60.38
60.44
60.47




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234721&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234721&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
156.87416666666670.5145069720056511.72
258.49583333333330.5530322747993081.84
359.67416666666670.279559989767470.940000000000005
460.72666666666670.3696025711572641.09
560.59666666666670.4102622959950751.08

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 56.8741666666667 & 0.514506972005651 & 1.72 \tabularnewline
2 & 58.4958333333333 & 0.553032274799308 & 1.84 \tabularnewline
3 & 59.6741666666667 & 0.27955998976747 & 0.940000000000005 \tabularnewline
4 & 60.7266666666667 & 0.369602571157264 & 1.09 \tabularnewline
5 & 60.5966666666667 & 0.410262295995075 & 1.08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234721&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]56.8741666666667[/C][C]0.514506972005651[/C][C]1.72[/C][/ROW]
[ROW][C]2[/C][C]58.4958333333333[/C][C]0.553032274799308[/C][C]1.84[/C][/ROW]
[ROW][C]3[/C][C]59.6741666666667[/C][C]0.27955998976747[/C][C]0.940000000000005[/C][/ROW]
[ROW][C]4[/C][C]60.7266666666667[/C][C]0.369602571157264[/C][C]1.09[/C][/ROW]
[ROW][C]5[/C][C]60.5966666666667[/C][C]0.410262295995075[/C][C]1.08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234721&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
156.87416666666670.5145069720056511.72
258.49583333333330.5530322747993081.84
359.67416666666670.279559989767470.940000000000005
460.72666666666670.3696025711572641.09
560.59666666666670.4102622959950751.08







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha3.12291341854474
beta-0.045509723532435
S.D.0.0296208211209092
T-STAT-1.53640992417695
p-value0.22202376492337

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 3.12291341854474 \tabularnewline
beta & -0.045509723532435 \tabularnewline
S.D. & 0.0296208211209092 \tabularnewline
T-STAT & -1.53640992417695 \tabularnewline
p-value & 0.22202376492337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234721&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.12291341854474[/C][/ROW]
[ROW][C]beta[/C][C]-0.045509723532435[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0296208211209092[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.53640992417695[/C][/ROW]
[ROW][C]p-value[/C][C]0.22202376492337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234721&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)
alpha3.12291341854474
beta-0.045509723532435
S.D.0.0296208211209092
T-STAT-1.53640992417695
p-value0.22202376492337







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha24.1452772533079
beta-6.13171349454508
S.D.4.53761324065095
T-STAT-1.35130809290072
p-value0.269467386516839
Lambda7.13171349454508

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 24.1452772533079 \tabularnewline
beta & -6.13171349454508 \tabularnewline
S.D. & 4.53761324065095 \tabularnewline
T-STAT & -1.35130809290072 \tabularnewline
p-value & 0.269467386516839 \tabularnewline
Lambda & 7.13171349454508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=234721&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]24.1452772533079[/C][/ROW]
[ROW][C]beta[/C][C]-6.13171349454508[/C][/ROW]
[ROW][C]S.D.[/C][C]4.53761324065095[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.35130809290072[/C][/ROW]
[ROW][C]p-value[/C][C]0.269467386516839[/C][/ROW]
[ROW][C]Lambda[/C][C]7.13171349454508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=234721&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=234721&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)
alpha24.1452772533079
beta-6.13171349454508
S.D.4.53761324065095
T-STAT-1.35130809290072
p-value0.269467386516839
Lambda7.13171349454508



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')