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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSat, 26 Nov 2016 10:10:37 +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/2016/Nov/26/t1480155059f5rwmsfmbxgogqt.htm/, Retrieved Fri, 03 May 2024 21:23:17 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 03 May 2024 21:23:17 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,78
97,73
97,61
97,69
97,68
97,67
97,67
97,96
98,27
99,52
99,59
99,75
99,75
99,8
99,99
100,25
100,08
100,08
100,08
100,06
101
101,81
101,82
101,96
101,96
101,93
102,03
102,11
102,07
102,34
102,34
102,33
102,77
103,08
103,38
103,44
99,1
99,15
99,21
99,01
99,08
99,11
100,11
100,31
100,55
101,38
101,49
101,5
100,69
100,8
100,58
100,34
100,38
100,33
101,06
101,15
101,36
101,98
102,24
102,34
101,91
101,8
101,8
101,73
101,8
101,81
102,28
101,7
101,7
102,37
102,43
102,41

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.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:  
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'Gertrude Mary Cox' @ cox.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.24333333333330.8503831578479872.14
2100.5566666666670.8474274796897562.20999999999999
3102.4816666666670.5491950031775151.50999999999999
41001.025156307372422.48999999999999
5101.1041666666670.7323990260324862.01000000000001
6101.9783333333330.2984454673297910.730000000000004

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.2433333333333 & 0.850383157847987 & 2.14 \tabularnewline
2 & 100.556666666667 & 0.847427479689756 & 2.20999999999999 \tabularnewline
3 & 102.481666666667 & 0.549195003177515 & 1.50999999999999 \tabularnewline
4 & 100 & 1.02515630737242 & 2.48999999999999 \tabularnewline
5 & 101.104166666667 & 0.732399026032486 & 2.01000000000001 \tabularnewline
6 & 101.978333333333 & 0.298445467329791 & 0.730000000000004 \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]98.2433333333333[/C][C]0.850383157847987[/C][C]2.14[/C][/ROW]
[ROW][C]2[/C][C]100.556666666667[/C][C]0.847427479689756[/C][C]2.20999999999999[/C][/ROW]
[ROW][C]3[/C][C]102.481666666667[/C][C]0.549195003177515[/C][C]1.50999999999999[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]1.02515630737242[/C][C]2.48999999999999[/C][/ROW]
[ROW][C]5[/C][C]101.104166666667[/C][C]0.732399026032486[/C][C]2.01000000000001[/C][/ROW]
[ROW][C]6[/C][C]101.978333333333[/C][C]0.298445467329791[/C][C]0.730000000000004[/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:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.24333333333330.8503831578479872.14
2100.5566666666670.8474274796897562.20999999999999
3102.4816666666670.5491950031775151.50999999999999
41001.025156307372422.48999999999999
5101.1041666666670.7323990260324862.01000000000001
6101.9783333333330.2984454673297910.730000000000004






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12.8774183255894
beta-0.120724403490864
S.D.0.0599568292061527
T-STAT-2.01352214733989
p-value0.11433878963157

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 12.8774183255894 \tabularnewline
beta & -0.120724403490864 \tabularnewline
S.D. & 0.0599568292061527 \tabularnewline
T-STAT & -2.01352214733989 \tabularnewline
p-value & 0.11433878963157 \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]12.8774183255894[/C][/ROW]
[ROW][C]beta[/C][C]-0.120724403490864[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0599568292061527[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.01352214733989[/C][/ROW]
[ROW][C]p-value[/C][C]0.11433878963157[/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:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha12.8774183255894
beta-0.120724403490864
S.D.0.0599568292061527
T-STAT-2.01352214733989
p-value0.11433878963157






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha90.4409672913214
beta-19.6960961207487
S.D.10.9745915266026
T-STAT-1.7946997000303
p-value0.147143272974004
Lambda20.6960961207487

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 90.4409672913214 \tabularnewline
beta & -19.6960961207487 \tabularnewline
S.D. & 10.9745915266026 \tabularnewline
T-STAT & -1.7946997000303 \tabularnewline
p-value & 0.147143272974004 \tabularnewline
Lambda & 20.6960961207487 \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]90.4409672913214[/C][/ROW]
[ROW][C]beta[/C][C]-19.6960961207487[/C][/ROW]
[ROW][C]S.D.[/C][C]10.9745915266026[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.7946997000303[/C][/ROW]
[ROW][C]p-value[/C][C]0.147143272974004[/C][/ROW]
[ROW][C]Lambda[/C][C]20.6960961207487[/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:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha90.4409672913214
beta-19.6960961207487
S.D.10.9745915266026
T-STAT-1.7946997000303
p-value0.147143272974004
Lambda20.6960961207487


Figures (Output of Computation)

Input Parameters & R Code

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')