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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 05 Dec 2013 14:24:49 -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/Dec/05/t13862715000i3t7d9t40hybub.htm/, Retrieved Fri, 19 Apr 2024 18:10:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231226, Retrieved Fri, 19 Apr 2024 18:10:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-05 19:24:49] [188bf81caccb86647293be436f272d1b] [Current]
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Dataseries X:
1.41
1.42
1.43
1.43
1.43
1.43
1.43
1.44
1.44
1.45
1.46
1.46
1.47
1.47
1.47
1.49
1.49
1.49
1.49
1.5
1.52
1.54
1.56
1.56
1.57
1.58
1.59
1.6
1.59
1.6
1.61
1.61
1.61
1.62
1.62
1.61
1.62
1.62
1.63
1.64
1.64
1.64
1.64
1.64
1.65
1.65
1.65
1.65
1.65
1.66
1.66
1.67
1.67
1.67
1.67
1.67
1.67
1.69
1.69
1.69
1.7
1.71
1.72
1.71
1.71
1.71
1.72
1.72
1.72
1.73
1.73
1.73
1.74
1.74
1.75
1.76
1.76
1.77
1.78
1.79
1.8
1.8
1.8
1.81




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231226&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231226&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231226&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.435833333333330.01505042031024890.05
21.504166666666670.03315482505220660.0900000000000001
31.600833333333330.01564279289951030.05
41.639166666666670.01083624669450830.0299999999999998
51.671666666666670.01267304464625850.04
61.71750.009653072991634240.03
71.7750.02504541329810170.0700000000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.43583333333333 & 0.0150504203102489 & 0.05 \tabularnewline
2 & 1.50416666666667 & 0.0331548250522066 & 0.0900000000000001 \tabularnewline
3 & 1.60083333333333 & 0.0156427928995103 & 0.05 \tabularnewline
4 & 1.63916666666667 & 0.0108362466945083 & 0.0299999999999998 \tabularnewline
5 & 1.67166666666667 & 0.0126730446462585 & 0.04 \tabularnewline
6 & 1.7175 & 0.00965307299163424 & 0.03 \tabularnewline
7 & 1.775 & 0.0250454132981017 & 0.0700000000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231226&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]1.43583333333333[/C][C]0.0150504203102489[/C][C]0.05[/C][/ROW]
[ROW][C]2[/C][C]1.50416666666667[/C][C]0.0331548250522066[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]3[/C][C]1.60083333333333[/C][C]0.0156427928995103[/C][C]0.05[/C][/ROW]
[ROW][C]4[/C][C]1.63916666666667[/C][C]0.0108362466945083[/C][C]0.0299999999999998[/C][/ROW]
[ROW][C]5[/C][C]1.67166666666667[/C][C]0.0126730446462585[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]1.7175[/C][C]0.00965307299163424[/C][C]0.03[/C][/ROW]
[ROW][C]7[/C][C]1.775[/C][C]0.0250454132981017[/C][C]0.0700000000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231226&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231226&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
11.435833333333330.01505042031024890.05
21.504166666666670.03315482505220660.0900000000000001
31.600833333333330.01564279289951030.05
41.639166666666670.01083624669450830.0299999999999998
51.671666666666670.01267304464625850.04
61.71750.009653072991634240.03
71.7750.02504541329810170.0700000000000001







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0424184778952112
beta-0.0154152821015802
S.D.0.0315981779985654
T-STAT-0.487853511752484
p-value0.646292494738496

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0424184778952112 \tabularnewline
beta & -0.0154152821015802 \tabularnewline
S.D. & 0.0315981779985654 \tabularnewline
T-STAT & -0.487853511752484 \tabularnewline
p-value & 0.646292494738496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231226&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0424184778952112[/C][/ROW]
[ROW][C]beta[/C][C]-0.0154152821015802[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0315981779985654[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.487853511752484[/C][/ROW]
[ROW][C]p-value[/C][C]0.646292494738496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231226&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231226&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)
alpha0.0424184778952112
beta-0.0154152821015802
S.D.0.0315981779985654
T-STAT-0.487853511752484
p-value0.646292494738496







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.45796988474365
beta-1.41994805132209
S.D.2.61483653713511
T-STAT-0.543035111815374
p-value0.610427842780054
Lambda2.41994805132209

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.45796988474365 \tabularnewline
beta & -1.41994805132209 \tabularnewline
S.D. & 2.61483653713511 \tabularnewline
T-STAT & -0.543035111815374 \tabularnewline
p-value & 0.610427842780054 \tabularnewline
Lambda & 2.41994805132209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231226&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.45796988474365[/C][/ROW]
[ROW][C]beta[/C][C]-1.41994805132209[/C][/ROW]
[ROW][C]S.D.[/C][C]2.61483653713511[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.543035111815374[/C][/ROW]
[ROW][C]p-value[/C][C]0.610427842780054[/C][/ROW]
[ROW][C]Lambda[/C][C]2.41994805132209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231226&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231226&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-3.45796988474365
beta-1.41994805132209
S.D.2.61483653713511
T-STAT-0.543035111815374
p-value0.610427842780054
Lambda2.41994805132209



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')