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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 computationMon, 28 Nov 2011 13:40:08 -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/2011/Nov/28/t1322505683e1p291nou4v3zsk.htm/, Retrieved Sat, 20 Apr 2024 04:30:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147960, Retrieved Sat, 20 Apr 2024 04:30:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W8
Estimated Impact80

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2011-11-28 18:40:08] [a37c4e2766dbfff97993810aa18b7ce1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
18.94
18.97
19
19.08
19.18
19.24
19.23
19.25
19.3
19.33
19.35
19.35
19.31
19.47
19.7
19.76
19.9
19.97
20.1
20.26
20.44
20.43
20.57
20.6
20.69
20.93
20.98
21.11
21.14
21.16
21.32
21.32
21.48
21.58
21.74
21.75
21.81
21.89
22.21
22.37
22.47
22.51
22.55
22.61
22.58
22.85
22.93
22.98
23.01
23.11
23.18
23.18
23.21
23.22
23.12
23.15
23.16
23.21
23.21
23.22
23.25
23.39
23.41
23.45
23.46
23.44
23.54
23.62
23.86
24.07
24.13
24.12

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=147960&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=147960&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147960&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
119.1850.1506048411632850.41
220.04250.430097769011991.29
321.26666666666670.3285044162795251.06
422.480.3697910958168881.17
523.1650.06171783299088570.209999999999997
623.6450.31477264522480.879999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 19.185 & 0.150604841163285 & 0.41 \tabularnewline
2 & 20.0425 & 0.43009776901199 & 1.29 \tabularnewline
3 & 21.2666666666667 & 0.328504416279525 & 1.06 \tabularnewline
4 & 22.48 & 0.369791095816888 & 1.17 \tabularnewline
5 & 23.165 & 0.0617178329908857 & 0.209999999999997 \tabularnewline
6 & 23.645 & 0.3147726452248 & 0.879999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147960&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]19.185[/C][C]0.150604841163285[/C][C]0.41[/C][/ROW]
[ROW][C]2[/C][C]20.0425[/C][C]0.43009776901199[/C][C]1.29[/C][/ROW]
[ROW][C]3[/C][C]21.2666666666667[/C][C]0.328504416279525[/C][C]1.06[/C][/ROW]
[ROW][C]4[/C][C]22.48[/C][C]0.369791095816888[/C][C]1.17[/C][/ROW]
[ROW][C]5[/C][C]23.165[/C][C]0.0617178329908857[/C][C]0.209999999999997[/C][/ROW]
[ROW][C]6[/C][C]23.645[/C][C]0.3147726452248[/C][C]0.879999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147960&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147960&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
119.1850.1506048411632850.41
220.04250.430097769011991.29
321.26666666666670.3285044162795251.06
422.480.3697910958168881.17
523.1650.06171783299088570.209999999999997
623.6450.31477264522480.879999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.451753115916286
beta-0.00812911252664623
S.D.0.0392960659403653
T-STAT-0.206868355193183
p-value0.846216625709288

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.451753115916286 \tabularnewline
beta & -0.00812911252664623 \tabularnewline
S.D. & 0.0392960659403653 \tabularnewline
T-STAT & -0.206868355193183 \tabularnewline
p-value & 0.846216625709288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147960&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.451753115916286[/C][/ROW]
[ROW][C]beta[/C][C]-0.00812911252664623[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0392960659403653[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.206868355193183[/C][/ROW]
[ROW][C]p-value[/C][C]0.846216625709288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147960&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147960&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)
alpha0.451753115916286
beta-0.00812911252664623
S.D.0.0392960659403653
T-STAT-0.206868355193183
p-value0.846216625709288






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha2.6959724480543
beta-1.35459077577674
S.D.4.41058297032899
T-STAT-0.307122841785175
p-value0.774074991275894
Lambda2.35459077577674

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.6959724480543 \tabularnewline
beta & -1.35459077577674 \tabularnewline
S.D. & 4.41058297032899 \tabularnewline
T-STAT & -0.307122841785175 \tabularnewline
p-value & 0.774074991275894 \tabularnewline
Lambda & 2.35459077577674 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147960&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.6959724480543[/C][/ROW]
[ROW][C]beta[/C][C]-1.35459077577674[/C][/ROW]
[ROW][C]S.D.[/C][C]4.41058297032899[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.307122841785175[/C][/ROW]
[ROW][C]p-value[/C][C]0.774074991275894[/C][/ROW]
[ROW][C]Lambda[/C][C]2.35459077577674[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147960&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147960&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)
alpha2.6959724480543
beta-1.35459077577674
S.D.4.41058297032899
T-STAT-0.307122841785175
p-value0.774074991275894
Lambda2.35459077577674


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')