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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 10 Jan 2009 09:59:16 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jan/10/t1231606824ihqoqsfqx64rl9q.htm/, Retrieved Thu, 31 Oct 2024 22:58:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36859, Retrieved Thu, 31 Oct 2024 22:58:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact290
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation Plot] [Opgave8 oefening ...] [2009-01-10 16:18:03] [74be16979710d4c4e7c6647856088456]
- RM D    [Standard Deviation-Mean Plot] [Opgave8 oefening ...] [2009-01-10 16:59:16] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
18.33
18.22
18.21
18.06
18.26
18.21
18.05
18.25
18.27
18.28
18.13
18.01
18.02
17.97
18.06
18.08
18.23
18.06
18.23
18.17
18.27
18.33
18.18
18.29
18.33
18.31
18.44
18.63
18.37
18.59
18.72
18.75
18.87
18.83
18.89
18.78
19.27
19.19
19.43
19.36
19.39
19.07
19.31
19.19
19.06
19.05
19.49
19.25
19.76
20.35
19.61
19.33
18.95
18.97
19.28
19.41
18.99
19.37
19.63
19.53
19.86
20.13
19.47
19.49
18.95
19.33
19.65
19.44
19.73
18.89
19.56
19.56




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36859&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36859&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36859&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
118.190.1030445622931250.319999999999997
218.15750.1168623899371320.359999999999999
318.62583333333330.2148343265839700.580000000000002
419.2550.1480479037952980.439999999999998
519.43166666666670.3942503434790311.40000000000000
619.5050.3460031529020821.24000000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 18.19 & 0.103044562293125 & 0.319999999999997 \tabularnewline
2 & 18.1575 & 0.116862389937132 & 0.359999999999999 \tabularnewline
3 & 18.6258333333333 & 0.214834326583970 & 0.580000000000002 \tabularnewline
4 & 19.255 & 0.148047903795298 & 0.439999999999998 \tabularnewline
5 & 19.4316666666667 & 0.394250343479031 & 1.40000000000000 \tabularnewline
6 & 19.505 & 0.346003152902082 & 1.24000000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36859&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]18.19[/C][C]0.103044562293125[/C][C]0.319999999999997[/C][/ROW]
[ROW][C]2[/C][C]18.1575[/C][C]0.116862389937132[/C][C]0.359999999999999[/C][/ROW]
[ROW][C]3[/C][C]18.6258333333333[/C][C]0.214834326583970[/C][C]0.580000000000002[/C][/ROW]
[ROW][C]4[/C][C]19.255[/C][C]0.148047903795298[/C][C]0.439999999999998[/C][/ROW]
[ROW][C]5[/C][C]19.4316666666667[/C][C]0.394250343479031[/C][C]1.40000000000000[/C][/ROW]
[ROW][C]6[/C][C]19.505[/C][C]0.346003152902082[/C][C]1.24000000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36859&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36859&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
118.190.1030445622931250.319999999999997
218.15750.1168623899371320.359999999999999
318.62583333333330.2148343265839700.580000000000002
419.2550.1480479037952980.439999999999998
519.43166666666670.3942503434790311.40000000000000
619.5050.3460031529020821.24000000000000







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-2.80828011705627
beta0.160586076802265
S.D.0.0595127629987671
T-STAT2.69834685386043
p-value0.0541870517476833

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -2.80828011705627 \tabularnewline
beta & 0.160586076802265 \tabularnewline
S.D. & 0.0595127629987671 \tabularnewline
T-STAT & 2.69834685386043 \tabularnewline
p-value & 0.0541870517476833 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36859&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.80828011705627[/C][/ROW]
[ROW][C]beta[/C][C]0.160586076802265[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0595127629987671[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.69834685386043[/C][/ROW]
[ROW][C]p-value[/C][C]0.0541870517476833[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36859&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36859&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-2.80828011705627
beta0.160586076802265
S.D.0.0595127629987671
T-STAT2.69834685386043
p-value0.0541870517476833







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-43.2388622162847
beta14.1643444932384
S.D.4.84800699475177
T-STAT2.92168400511222
p-value0.0431707617299387
Lambda-13.1643444932384

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -43.2388622162847 \tabularnewline
beta & 14.1643444932384 \tabularnewline
S.D. & 4.84800699475177 \tabularnewline
T-STAT & 2.92168400511222 \tabularnewline
p-value & 0.0431707617299387 \tabularnewline
Lambda & -13.1643444932384 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36859&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-43.2388622162847[/C][/ROW]
[ROW][C]beta[/C][C]14.1643444932384[/C][/ROW]
[ROW][C]S.D.[/C][C]4.84800699475177[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.92168400511222[/C][/ROW]
[ROW][C]p-value[/C][C]0.0431707617299387[/C][/ROW]
[ROW][C]Lambda[/C][C]-13.1643444932384[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36859&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36859&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-43.2388622162847
beta14.1643444932384
S.D.4.84800699475177
T-STAT2.92168400511222
p-value0.0431707617299387
Lambda-13.1643444932384



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')