Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationTue, 25 Apr 2017 21:38:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/25/t1493152699zngq4nu3uhpe74t.htm/, Retrieved Sat, 11 May 2024 08:03:31 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 11 May 2024 08:03:31 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
94.72
95.76
96.14
97.11
97.19
97.43
97.43
97.56
97.66
97.75
97.82
97.82
97.82
98.35
98.19
98.19
98.21
98.22
98.26
98.23
98.26
98.5
98.51
98.51
98.51
98.89
99.55
99.9
100.12
100.09
100.09
100.09
100.46
100.71
100.79
100.79
100.93
101.15
101.53
101.91
102.18
102.24
102.2
102.32
102.43
102.45
102.84
102.96
102.96
103.1
103.4
103.74
103.97
104.29
104.33
104.46
104.9
105.31
105.63
105.68
105.87
106.34
106.6
107.1
107.06
107.4
107.4
107.43
107.75
107.84
107.97
108.04




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
197.03250.9787480407503893.09999999999999
298.27083333333330.190141494363510.690000000000012
399.99916666666670.7177801427549612.28
4102.0950.6204910079196062.02999999999999
5104.3141666666670.9315525489821582.72000000000001
6107.2333333333330.6761029148843782.17

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 97.0325 & 0.978748040750389 & 3.09999999999999 \tabularnewline
2 & 98.2708333333333 & 0.19014149436351 & 0.690000000000012 \tabularnewline
3 & 99.9991666666667 & 0.717780142754961 & 2.28 \tabularnewline
4 & 102.095 & 0.620491007919606 & 2.02999999999999 \tabularnewline
5 & 104.314166666667 & 0.931552548982158 & 2.72000000000001 \tabularnewline
6 & 107.233333333333 & 0.676102914884378 & 2.17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]97.0325[/C][C]0.978748040750389[/C][C]3.09999999999999[/C][/ROW]
[ROW][C]2[/C][C]98.2708333333333[/C][C]0.19014149436351[/C][C]0.690000000000012[/C][/ROW]
[ROW][C]3[/C][C]99.9991666666667[/C][C]0.717780142754961[/C][C]2.28[/C][/ROW]
[ROW][C]4[/C][C]102.095[/C][C]0.620491007919606[/C][C]2.02999999999999[/C][/ROW]
[ROW][C]5[/C][C]104.314166666667[/C][C]0.931552548982158[/C][C]2.72000000000001[/C][/ROW]
[ROW][C]6[/C][C]107.233333333333[/C][C]0.676102914884378[/C][C]2.17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
197.03250.9787480407503893.09999999999999
298.27083333333330.190141494363510.690000000000012
399.99916666666670.7177801427549612.28
4102.0950.6204910079196062.02999999999999
5104.3141666666670.9315525489821582.72000000000001
6107.2333333333330.6761029148843782.17







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.47096138404101
beta0.0113977197512108
S.D.0.0362437721212809
T-STAT0.31447388293556
p-value0.768880998302623

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.47096138404101 \tabularnewline
beta & 0.0113977197512108 \tabularnewline
S.D. & 0.0362437721212809 \tabularnewline
T-STAT & 0.31447388293556 \tabularnewline
p-value & 0.768880998302623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.47096138404101[/C][/ROW]
[ROW][C]beta[/C][C]0.0113977197512108[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0362437721212809[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.31447388293556[/C][/ROW]
[ROW][C]p-value[/C][C]0.768880998302623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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-0.47096138404101
beta0.0113977197512108
S.D.0.0362437721212809
T-STAT0.31447388293556
p-value0.768880998302623







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-20.8944417708719
beta4.4166876834639
S.D.7.6510493922759
T-STAT0.577265608548124
p-value0.594694145915625
Lambda-3.4166876834639

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -20.8944417708719 \tabularnewline
beta & 4.4166876834639 \tabularnewline
S.D. & 7.6510493922759 \tabularnewline
T-STAT & 0.577265608548124 \tabularnewline
p-value & 0.594694145915625 \tabularnewline
Lambda & -3.4166876834639 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-20.8944417708719[/C][/ROW]
[ROW][C]beta[/C][C]4.4166876834639[/C][/ROW]
[ROW][C]S.D.[/C][C]7.6510493922759[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.577265608548124[/C][/ROW]
[ROW][C]p-value[/C][C]0.594694145915625[/C][/ROW]
[ROW][C]Lambda[/C][C]-3.4166876834639[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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-20.8944417708719
beta4.4166876834639
S.D.7.6510493922759
T-STAT0.577265608548124
p-value0.594694145915625
Lambda-3.4166876834639



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')