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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, 04 Dec 2013 05:03:01 -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/04/t13861513905ol8lkcu87zq396.htm/, Retrieved Thu, 25 Apr 2024 17:04:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230477, Retrieved Thu, 25 Apr 2024 17:04:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2013-12-04 10:03:01] [f0ec65ab0c213345bf099e498b60e56c] [Current]
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Dataseries X:
1.93
2.02
1.85
1.77
1.81
1.67
1.55
1.62
1.79
1.73
1.77
1.95
2.08
2.26
2.02
1.9
1.97
1.76
1.93
1.91
1.96
1.99
1.98
1.96
1.95
2.26
2.07
2.02
2.07
1.88
1.75
1.78
1.87
1.94
2.03
2.13
2.04
2.18
2.02
1.99
2.09
1.88
1.8
1.77
1.85
1.9
2.03
2.02
2.09
2.3
2.16
2.02
2.31
1.98
1.74
1.82
2.07
2.04
2.07
2.13
2.14
2.43
2.26
2.11
2.19
2.04
2.04
2.05
2.08
1.98
2.07
2.12
2.15
2.35
2.19
2.17
2.3
2.09
1.95
1.89
1.95
1.98
1.95
2.06




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230477&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]4 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=230477&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230477&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.788333333333330.1373008199229530.47
21.976666666666670.1179625004615940.5
31.979166666666670.1473066272244480.51
41.964166666666670.1236901064121230.41
52.060833333333330.166376262147160.57
62.125833333333330.1213903046400580.45
72.085833333333330.1487192799956490.46

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.78833333333333 & 0.137300819922953 & 0.47 \tabularnewline
2 & 1.97666666666667 & 0.117962500461594 & 0.5 \tabularnewline
3 & 1.97916666666667 & 0.147306627224448 & 0.51 \tabularnewline
4 & 1.96416666666667 & 0.123690106412123 & 0.41 \tabularnewline
5 & 2.06083333333333 & 0.16637626214716 & 0.57 \tabularnewline
6 & 2.12583333333333 & 0.121390304640058 & 0.45 \tabularnewline
7 & 2.08583333333333 & 0.148719279995649 & 0.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230477&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]1.78833333333333[/C][C]0.137300819922953[/C][C]0.47[/C][/ROW]
[ROW][C]2[/C][C]1.97666666666667[/C][C]0.117962500461594[/C][C]0.5[/C][/ROW]
[ROW][C]3[/C][C]1.97916666666667[/C][C]0.147306627224448[/C][C]0.51[/C][/ROW]
[ROW][C]4[/C][C]1.96416666666667[/C][C]0.123690106412123[/C][C]0.41[/C][/ROW]
[ROW][C]5[/C][C]2.06083333333333[/C][C]0.16637626214716[/C][C]0.57[/C][/ROW]
[ROW][C]6[/C][C]2.12583333333333[/C][C]0.121390304640058[/C][C]0.45[/C][/ROW]
[ROW][C]7[/C][C]2.08583333333333[/C][C]0.148719279995649[/C][C]0.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230477&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230477&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
11.788333333333330.1373008199229530.47
21.976666666666670.1179625004615940.5
31.979166666666670.1473066272244480.51
41.964166666666670.1236901064121230.41
52.060833333333330.166376262147160.57
62.125833333333330.1213903046400580.45
72.085833333333330.1487192799956490.46







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0974966393056406
beta0.0200466895629374
S.D.0.070907185802237
T-STAT0.282717320341107
p-value0.788723876020996

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0974966393056406 \tabularnewline
beta & 0.0200466895629374 \tabularnewline
S.D. & 0.070907185802237 \tabularnewline
T-STAT & 0.282717320341107 \tabularnewline
p-value & 0.788723876020996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230477&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0974966393056406[/C][/ROW]
[ROW][C]beta[/C][C]0.0200466895629374[/C][/ROW]
[ROW][C]S.D.[/C][C]0.070907185802237[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.282717320341107[/C][/ROW]
[ROW][C]p-value[/C][C]0.788723876020996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230477&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230477&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)
alpha0.0974966393056406
beta0.0200466895629374
S.D.0.070907185802237
T-STAT0.282717320341107
p-value0.788723876020996







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.1482864126274
beta0.227996011884137
S.D.0.994950391881209
T-STAT0.229153145467939
p-value0.827828261415302
Lambda0.772003988115863

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.1482864126274 \tabularnewline
beta & 0.227996011884137 \tabularnewline
S.D. & 0.994950391881209 \tabularnewline
T-STAT & 0.229153145467939 \tabularnewline
p-value & 0.827828261415302 \tabularnewline
Lambda & 0.772003988115863 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230477&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.1482864126274[/C][/ROW]
[ROW][C]beta[/C][C]0.227996011884137[/C][/ROW]
[ROW][C]S.D.[/C][C]0.994950391881209[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.229153145467939[/C][/ROW]
[ROW][C]p-value[/C][C]0.827828261415302[/C][/ROW]
[ROW][C]Lambda[/C][C]0.772003988115863[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230477&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230477&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-2.1482864126274
beta0.227996011884137
S.D.0.994950391881209
T-STAT0.229153145467939
p-value0.827828261415302
Lambda0.772003988115863



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')