Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 04 Dec 2009 05:35:15 -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/Dec/04/t1259930186n35m8q9yiz4ioul.htm/, Retrieved Sun, 28 Apr 2024 05:35:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63420, Retrieved Sun, 28 Apr 2024 05:35:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D      [Standard Deviation-Mean Plot] [workshop 9] [2009-12-04 12:35:15] [e81f30a5c3daacfe71a556c99a478849] [Current]
Feedback Forum

Post a new message
Dataseries X:
6.9
6.8
6.7
6.6
6.5
6.5
7.0
7.5
7.6
7.6
7.6
7.8
8.0
8.0
8.0
7.9
7.9
8.0
8.5
9.2
9.4
9.5
9.5
9.6
9.7
9.7
9.6
9.5
9.4
9.3
9.6
10.2
10.2
10.1
9.9
9.8
9.8
9.7
9.5
9.3
9.1
9.0
9.5
10.0
10.2
10.1
10.0
9.9
10.0
9.9
9.7
9.5
9.2
9.0
9.3
9.8
9.8
9.6
9.4
9.3
9.2
9.2
9.0
8.8
8.7
8.7
9.1
9.7
9.8
9.6
9.4
9.4
9.5
9.4
9.3
9.2
9.0
8.9
9.2
9.8
9.9
9.6
9.2
9.1
9.1
9.0
8.9
8.7
8.5
8.3
8.5
8.7
8.4
8.1
7.8
7.7
7.5
7.2
6.8
6.7
6.4
6.3
6.8
7.3
7.1
7.0
6.8
6.6
6.3
6.1
6.1
6.3
6.3
6.0
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.0
8.2
8.1
8.1
8.0
7.9
7.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63420&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63420&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63420&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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
17.091666666666670.4925967063953181.3
28.6250.7411600244334431.7
39.750.30.899999999999999
49.6750.3957156922474881.2
59.541666666666670.3088345639315461
69.216666666666670.3761849963982501.10000000000000
79.341666666666670.3088345639315461
88.4750.4454313537562111.4
96.8750.3596083728421541.2
106.591666666666670.6022055422789761.6
117.5250.4535215741084631.4
128.1750.32787192621511
138.391666666666670.7128155866744642.1
148.433333333333330.2461829819586650.799999999999999
158.250.3030151511363440.799999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.09166666666667 & 0.492596706395318 & 1.3 \tabularnewline
2 & 8.625 & 0.741160024433443 & 1.7 \tabularnewline
3 & 9.75 & 0.3 & 0.899999999999999 \tabularnewline
4 & 9.675 & 0.395715692247488 & 1.2 \tabularnewline
5 & 9.54166666666667 & 0.308834563931546 & 1 \tabularnewline
6 & 9.21666666666667 & 0.376184996398250 & 1.10000000000000 \tabularnewline
7 & 9.34166666666667 & 0.308834563931546 & 1 \tabularnewline
8 & 8.475 & 0.445431353756211 & 1.4 \tabularnewline
9 & 6.875 & 0.359608372842154 & 1.2 \tabularnewline
10 & 6.59166666666667 & 0.602205542278976 & 1.6 \tabularnewline
11 & 7.525 & 0.453521574108463 & 1.4 \tabularnewline
12 & 8.175 & 0.3278719262151 & 1 \tabularnewline
13 & 8.39166666666667 & 0.712815586674464 & 2.1 \tabularnewline
14 & 8.43333333333333 & 0.246182981958665 & 0.799999999999999 \tabularnewline
15 & 8.25 & 0.303015151136344 & 0.799999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63420&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]7.09166666666667[/C][C]0.492596706395318[/C][C]1.3[/C][/ROW]
[ROW][C]2[/C][C]8.625[/C][C]0.741160024433443[/C][C]1.7[/C][/ROW]
[ROW][C]3[/C][C]9.75[/C][C]0.3[/C][C]0.899999999999999[/C][/ROW]
[ROW][C]4[/C][C]9.675[/C][C]0.395715692247488[/C][C]1.2[/C][/ROW]
[ROW][C]5[/C][C]9.54166666666667[/C][C]0.308834563931546[/C][C]1[/C][/ROW]
[ROW][C]6[/C][C]9.21666666666667[/C][C]0.376184996398250[/C][C]1.10000000000000[/C][/ROW]
[ROW][C]7[/C][C]9.34166666666667[/C][C]0.308834563931546[/C][C]1[/C][/ROW]
[ROW][C]8[/C][C]8.475[/C][C]0.445431353756211[/C][C]1.4[/C][/ROW]
[ROW][C]9[/C][C]6.875[/C][C]0.359608372842154[/C][C]1.2[/C][/ROW]
[ROW][C]10[/C][C]6.59166666666667[/C][C]0.602205542278976[/C][C]1.6[/C][/ROW]
[ROW][C]11[/C][C]7.525[/C][C]0.453521574108463[/C][C]1.4[/C][/ROW]
[ROW][C]12[/C][C]8.175[/C][C]0.3278719262151[/C][C]1[/C][/ROW]
[ROW][C]13[/C][C]8.39166666666667[/C][C]0.712815586674464[/C][C]2.1[/C][/ROW]
[ROW][C]14[/C][C]8.43333333333333[/C][C]0.246182981958665[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]15[/C][C]8.25[/C][C]0.303015151136344[/C][C]0.799999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63420&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63420&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
17.091666666666670.4925967063953181.3
28.6250.7411600244334431.7
39.750.30.899999999999999
49.6750.3957156922474881.2
59.541666666666670.3088345639315461
69.216666666666670.3761849963982501.10000000000000
79.341666666666670.3088345639315461
88.4750.4454313537562111.4
96.8750.3596083728421541.2
106.591666666666670.6022055422789761.6
117.5250.4535215741084631.4
128.1750.32787192621511
138.391666666666670.7128155866744642.1
148.433333333333330.2461829819586650.799999999999999
158.250.3030151511363440.799999999999999







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.840273446315694
beta-0.0494617743308828
S.D.0.0392737385545973
T-STAT-1.25941089774589
p-value0.230025002572254

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.840273446315694 \tabularnewline
beta & -0.0494617743308828 \tabularnewline
S.D. & 0.0392737385545973 \tabularnewline
T-STAT & -1.25941089774589 \tabularnewline
p-value & 0.230025002572254 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63420&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.840273446315694[/C][/ROW]
[ROW][C]beta[/C][C]-0.0494617743308828[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0392737385545973[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.25941089774589[/C][/ROW]
[ROW][C]p-value[/C][C]0.230025002572254[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63420&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63420&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)
alpha0.840273446315694
beta-0.0494617743308828
S.D.0.0392737385545973
T-STAT-1.25941089774589
p-value0.230025002572254







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha1.13891688566029
beta-0.965963750692966
S.D.0.683807493691728
T-STAT-1.41262527773414
p-value0.181256937345484
Lambda1.96596375069297

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 1.13891688566029 \tabularnewline
beta & -0.965963750692966 \tabularnewline
S.D. & 0.683807493691728 \tabularnewline
T-STAT & -1.41262527773414 \tabularnewline
p-value & 0.181256937345484 \tabularnewline
Lambda & 1.96596375069297 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63420&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.13891688566029[/C][/ROW]
[ROW][C]beta[/C][C]-0.965963750692966[/C][/ROW]
[ROW][C]S.D.[/C][C]0.683807493691728[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.41262527773414[/C][/ROW]
[ROW][C]p-value[/C][C]0.181256937345484[/C][/ROW]
[ROW][C]Lambda[/C][C]1.96596375069297[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63420&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63420&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)
alpha1.13891688566029
beta-0.965963750692966
S.D.0.683807493691728
T-STAT-1.41262527773414
p-value0.181256937345484
Lambda1.96596375069297



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')