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Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 29 Nov 2015 09:03:10 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/29/t1448787894z9lpc9h2cmjq8lw.htm/, Retrieved Thu, 16 May 2024 00:06:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284398, Retrieved Thu, 16 May 2024 00:06:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2015-11-29 09:03:10] [935c69a10ec4a64678755fcf1ddf3064] [Current]
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Dataseries X:
0,62
0,7
1,65
1,79
2,28
2,46
2,57
2,32
2,91
3,01
2,87
3,11
3,22
3,38
3,52
3,41
3,35
3,68
3,75
3,6
3,56
3,57
3,85
3,48
3,65
3,66
3,36
3,19
2,81
2,25
2,32
2,85
2,75
2,78
2,26
2,23
1,46
1,19
1,11
1
1,18
1,59
1,51
1,01
0,9
0,63
0,81
0,97
1,14
0,97
0,89
0,62
0,36
0,27
0,34
0,02
-0,12
0,09
-0,11
-0,38




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284398&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]1 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=284398&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284398&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
12.190833333333330.8463016691177652.49
23.530833333333330.1780428106502550.63
32.84250.5275177722124631.43
41.113333333333330.2908086947972790.96
50.3408333333333330.4786811110338551.52

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2.19083333333333 & 0.846301669117765 & 2.49 \tabularnewline
2 & 3.53083333333333 & 0.178042810650255 & 0.63 \tabularnewline
3 & 2.8425 & 0.527517772212463 & 1.43 \tabularnewline
4 & 1.11333333333333 & 0.290808694797279 & 0.96 \tabularnewline
5 & 0.340833333333333 & 0.478681111033855 & 1.52 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284398&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]2.19083333333333[/C][C]0.846301669117765[/C][C]2.49[/C][/ROW]
[ROW][C]2[/C][C]3.53083333333333[/C][C]0.178042810650255[/C][C]0.63[/C][/ROW]
[ROW][C]3[/C][C]2.8425[/C][C]0.527517772212463[/C][C]1.43[/C][/ROW]
[ROW][C]4[/C][C]1.11333333333333[/C][C]0.290808694797279[/C][C]0.96[/C][/ROW]
[ROW][C]5[/C][C]0.340833333333333[/C][C]0.478681111033855[/C][C]1.52[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284398&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284398&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
12.190833333333330.8463016691177652.49
23.530833333333330.1780428106502550.63
32.84250.5275177722124631.43
41.113333333333330.2908086947972790.96
50.3408333333333330.4786811110338551.52







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.519309751038392
beta-0.0274693093375823
S.D.0.113720140593828
T-STAT-0.241551841161486
p-value0.824696751586593

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.519309751038392 \tabularnewline
beta & -0.0274693093375823 \tabularnewline
S.D. & 0.113720140593828 \tabularnewline
T-STAT & -0.241551841161486 \tabularnewline
p-value & 0.824696751586593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284398&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.519309751038392[/C][/ROW]
[ROW][C]beta[/C][C]-0.0274693093375823[/C][/ROW]
[ROW][C]S.D.[/C][C]0.113720140593828[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.241551841161486[/C][/ROW]
[ROW][C]p-value[/C][C]0.824696751586593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284398&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284398&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)
alpha0.519309751038392
beta-0.0274693093375823
S.D.0.113720140593828
T-STAT-0.241551841161486
p-value0.824696751586593







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.852673326489405
beta-0.113423233901047
S.D.0.35908766184284
T-STAT-0.315865026715088
p-value0.772804655287686
Lambda1.11342323390105

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.852673326489405 \tabularnewline
beta & -0.113423233901047 \tabularnewline
S.D. & 0.35908766184284 \tabularnewline
T-STAT & -0.315865026715088 \tabularnewline
p-value & 0.772804655287686 \tabularnewline
Lambda & 1.11342323390105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284398&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.852673326489405[/C][/ROW]
[ROW][C]beta[/C][C]-0.113423233901047[/C][/ROW]
[ROW][C]S.D.[/C][C]0.35908766184284[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.315865026715088[/C][/ROW]
[ROW][C]p-value[/C][C]0.772804655287686[/C][/ROW]
[ROW][C]Lambda[/C][C]1.11342323390105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284398&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284398&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-0.852673326489405
beta-0.113423233901047
S.D.0.35908766184284
T-STAT-0.315865026715088
p-value0.772804655287686
Lambda1.11342323390105



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')