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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationMon, 12 Dec 2011 15:05:51 -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/2011/Dec/12/t1323720406tfmigysfyrh399g.htm/, Retrieved Fri, 03 May 2024 10:35:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154192, Retrieved Fri, 03 May 2024 10:35:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact72
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [Oefening 8 eigen ...] [2011-12-12 20:05:51] [060caeb40c68cbb867cbfbfe8deeeb10] [Current]
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Dataseries X:
74.96
75.19
74.98
75.54
75.61
75.59
75.58
75.44
75.37
75.22
75.33
75.33
78.33
78.09
77.88
77.61
77.43
77.47
77.47
77.46
77.76
78.29
78.56
78.55
78.55
78.59
77.95
78.5
78.45
78.31
78.31
78.33
78.28
79.06
79.2
79.26
79.26
79.38
79.35
78.91
79.11
79.22
79.22
79.21
79.26
79.82
80.04
80.2
80.2
80.27
80.37
80.57
79.99
79.86
79.86
79.81
79.88
80.2
80.53
80.52
80.52
80.48
80.29
79.54
79.39
79.3
79.3
79.49
79.63
79.74
80.17
80.06




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154192&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154192&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154192&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'George Udny Yule' @ yule.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
175.3450.2245601761828510.650000000000006
277.90833333333330.4388794270812341.13
378.56583333333330.4038779818737651.31
479.4150.3920227266139291.29000000000001
580.17166666666670.2863828757365760.759999999999991
679.82583333333330.4554410117144881.22

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 75.345 & 0.224560176182851 & 0.650000000000006 \tabularnewline
2 & 77.9083333333333 & 0.438879427081234 & 1.13 \tabularnewline
3 & 78.5658333333333 & 0.403877981873765 & 1.31 \tabularnewline
4 & 79.415 & 0.392022726613929 & 1.29000000000001 \tabularnewline
5 & 80.1716666666667 & 0.286382875736576 & 0.759999999999991 \tabularnewline
6 & 79.8258333333333 & 0.455441011714488 & 1.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154192&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]75.345[/C][C]0.224560176182851[/C][C]0.650000000000006[/C][/ROW]
[ROW][C]2[/C][C]77.9083333333333[/C][C]0.438879427081234[/C][C]1.13[/C][/ROW]
[ROW][C]3[/C][C]78.5658333333333[/C][C]0.403877981873765[/C][C]1.31[/C][/ROW]
[ROW][C]4[/C][C]79.415[/C][C]0.392022726613929[/C][C]1.29000000000001[/C][/ROW]
[ROW][C]5[/C][C]80.1716666666667[/C][C]0.286382875736576[/C][C]0.759999999999991[/C][/ROW]
[ROW][C]6[/C][C]79.8258333333333[/C][C]0.455441011714488[/C][C]1.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154192&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154192&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
175.3450.2245601761828510.650000000000006
277.90833333333330.4388794270812341.13
378.56583333333330.4038779818737651.31
479.4150.3920227266139291.29000000000001
580.17166666666670.2863828757365760.759999999999991
679.82583333333330.4554410117144881.22







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-1.70920185110297
beta0.0264336550086561
S.D.0.0221538321765465
T-STAT1.19318656916795
p-value0.298729389895128

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -1.70920185110297 \tabularnewline
beta & 0.0264336550086561 \tabularnewline
S.D. & 0.0221538321765465 \tabularnewline
T-STAT & 1.19318656916795 \tabularnewline
p-value & 0.298729389895128 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154192&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.70920185110297[/C][/ROW]
[ROW][C]beta[/C][C]0.0264336550086561[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0221538321765465[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.19318656916795[/C][/ROW]
[ROW][C]p-value[/C][C]0.298729389895128[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154192&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154192&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-1.70920185110297
beta0.0264336550086561
S.D.0.0221538321765465
T-STAT1.19318656916795
p-value0.298729389895128







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-31.3896559250666
beta6.95718286701752
S.D.5.0351814792862
T-STAT1.38171442194051
p-value0.239215903685245
Lambda-5.95718286701752

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -31.3896559250666 \tabularnewline
beta & 6.95718286701752 \tabularnewline
S.D. & 5.0351814792862 \tabularnewline
T-STAT & 1.38171442194051 \tabularnewline
p-value & 0.239215903685245 \tabularnewline
Lambda & -5.95718286701752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154192&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-31.3896559250666[/C][/ROW]
[ROW][C]beta[/C][C]6.95718286701752[/C][/ROW]
[ROW][C]S.D.[/C][C]5.0351814792862[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.38171442194051[/C][/ROW]
[ROW][C]p-value[/C][C]0.239215903685245[/C][/ROW]
[ROW][C]Lambda[/C][C]-5.95718286701752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154192&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154192&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-31.3896559250666
beta6.95718286701752
S.D.5.0351814792862
T-STAT1.38171442194051
p-value0.239215903685245
Lambda-5.95718286701752



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')