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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationWed, 09 Jan 2013 20:50:29 -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/2013/Jan/09/t1357782675qtdgnx2ycex2o9k.htm/, Retrieved Fri, 01 Nov 2024 00:38:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205126, Retrieved Fri, 01 Nov 2024 00:38:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Opgave 8 oef 3 St...] [2013-01-10 01:50:29] [40325e7317026cf0d36242170f65df44] [Current]
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Dataseries X:
101.81
101.72
101.78
102.04
102.36
102.56
102.69
102.77
102.85
102.9
102.72
102.79
102.9
102.91
103.29
103.35
102.97
103.05
103.18
103.21
103.32
103.31
103.6
103.68
103.77
103.82
103.86
103.9
103.63
103.65
103.7
103.77
103.94
104.03
104.03
104.29
104.35
104.67
104.73
104.86
104.05
104.15
104.27
104.33
104.41
104.4
104.41
104.6
104.61
104.65
104.55
104.51
104.74
104.89
104.91
104.93
104.95
104.97
105.16
105.29
105.35
105.36
105.45
105.3
105.73
105.86
105.85
105.95
105.97
106.15
105.37
105.39




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205126&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205126&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205126&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'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1102.4158333333330.4549417212093981.18000000000001
2103.2308333333330.2497438081253860.780000000000001
3103.8658333333330.1884606702801010.660000000000011
4104.4358333333330.2388403168849370.810000000000002
5104.8466666666670.2413723390544290.780000000000001
6105.6441666666670.3037779791328880.850000000000009

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.415833333333 & 0.454941721209398 & 1.18000000000001 \tabularnewline
2 & 103.230833333333 & 0.249743808125386 & 0.780000000000001 \tabularnewline
3 & 103.865833333333 & 0.188460670280101 & 0.660000000000011 \tabularnewline
4 & 104.435833333333 & 0.238840316884937 & 0.810000000000002 \tabularnewline
5 & 104.846666666667 & 0.241372339054429 & 0.780000000000001 \tabularnewline
6 & 105.644166666667 & 0.303777979132888 & 0.850000000000009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205126&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]102.415833333333[/C][C]0.454941721209398[/C][C]1.18000000000001[/C][/ROW]
[ROW][C]2[/C][C]103.230833333333[/C][C]0.249743808125386[/C][C]0.780000000000001[/C][/ROW]
[ROW][C]3[/C][C]103.865833333333[/C][C]0.188460670280101[/C][C]0.660000000000011[/C][/ROW]
[ROW][C]4[/C][C]104.435833333333[/C][C]0.238840316884937[/C][C]0.810000000000002[/C][/ROW]
[ROW][C]5[/C][C]104.846666666667[/C][C]0.241372339054429[/C][C]0.780000000000001[/C][/ROW]
[ROW][C]6[/C][C]105.644166666667[/C][C]0.303777979132888[/C][C]0.850000000000009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205126&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205126&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
1102.4158333333330.4549417212093981.18000000000001
2103.2308333333330.2497438081253860.780000000000001
3103.8658333333330.1884606702801010.660000000000011
4104.4358333333330.2388403168849370.810000000000002
5104.8466666666670.2413723390544290.780000000000001
6105.6441666666670.3037779791328880.850000000000009







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha4.20992285397242
beta-0.0377657289100444
S.D.0.0356770960010504
T-STAT-1.05854268264807
p-value0.349496744748132

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 4.20992285397242 \tabularnewline
beta & -0.0377657289100444 \tabularnewline
S.D. & 0.0356770960010504 \tabularnewline
T-STAT & -1.05854268264807 \tabularnewline
p-value & 0.349496744748132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205126&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]4.20992285397242[/C][/ROW]
[ROW][C]beta[/C][C]-0.0377657289100444[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0356770960010504[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.05854268264807[/C][/ROW]
[ROW][C]p-value[/C][C]0.349496744748132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205126&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205126&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)
alpha4.20992285397242
beta-0.0377657289100444
S.D.0.0356770960010504
T-STAT-1.05854268264807
p-value0.349496744748132







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha47.5812056811872
beta-10.5264847698053
S.D.12.3920404893173
T-STAT-0.849455324075143
p-value0.44347932849336
Lambda11.5264847698053

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 47.5812056811872 \tabularnewline
beta & -10.5264847698053 \tabularnewline
S.D. & 12.3920404893173 \tabularnewline
T-STAT & -0.849455324075143 \tabularnewline
p-value & 0.44347932849336 \tabularnewline
Lambda & 11.5264847698053 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205126&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]47.5812056811872[/C][/ROW]
[ROW][C]beta[/C][C]-10.5264847698053[/C][/ROW]
[ROW][C]S.D.[/C][C]12.3920404893173[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.849455324075143[/C][/ROW]
[ROW][C]p-value[/C][C]0.44347932849336[/C][/ROW]
[ROW][C]Lambda[/C][C]11.5264847698053[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205126&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205126&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)
alpha47.5812056811872
beta-10.5264847698053
S.D.12.3920404893173
T-STAT-0.849455324075143
p-value0.44347932849336
Lambda11.5264847698053



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')