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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 computationFri, 27 Nov 2009 10:40:19 -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/Nov/27/t1259343692bc5ntpwfswgatm3.htm/, Retrieved Mon, 29 Apr 2024 18:21:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61049, Retrieved Mon, 29 Apr 2024 18:21:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2009-11-27 16:33:53] [a8dc04902f2584d6dc8a82e937850322]
- RMP     [Standard Deviation-Mean Plot] [] [2009-11-27 17:40:19] [8803431e497d94425e57d35981fe4f1d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.008	
9.169	
8.788	
8.417	
8.247	
8.197	
8.236	
8.253	
7.733	
8.366	
8.626	
8.863	
10.102	
8.463	
9.114	
8.563	
8.872	
8.301	
8.301	
8.278	
7.736	
7.973	
8.268	
9.476	
11.100	
8.962	
9.173	
8.738	
8.459	
8.078	
8.411	
8.291	
7.810	
8.616	
8.312	
9.692	
9.911	
8.915	
9.452	
9.112	
8.472	
8.230	
8.384	
8.625	
8.221	
8.649	
8.625	
10.443	
10.357	
8.586	
8.892	
8.329	
8.101	
7.922	
8.120	
7.838	
7.735	
8.406	
8.209	
9.451	
10.041	
9.411	
10.405	
8.467	
8.464	
8.102	
7.627	
7.513	
7.510	
8.291	
8.064	
9.383

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'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=61049&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=61049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61049&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
18.741916666666671.094680813448994.275
28.620583333333330.6680329956920792.366
38.80350.8818782125771013.29
48.919916666666670.6955517702885352.222
58.49550.7566420433852342.622
68.60650.9811020241637372.895

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 8.74191666666667 & 1.09468081344899 & 4.275 \tabularnewline
2 & 8.62058333333333 & 0.668032995692079 & 2.366 \tabularnewline
3 & 8.8035 & 0.881878212577101 & 3.29 \tabularnewline
4 & 8.91991666666667 & 0.695551770288535 & 2.222 \tabularnewline
5 & 8.4955 & 0.756642043385234 & 2.622 \tabularnewline
6 & 8.6065 & 0.981102024163737 & 2.895 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61049&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]8.74191666666667[/C][C]1.09468081344899[/C][C]4.275[/C][/ROW]
[ROW][C]2[/C][C]8.62058333333333[/C][C]0.668032995692079[/C][C]2.366[/C][/ROW]
[ROW][C]3[/C][C]8.8035[/C][C]0.881878212577101[/C][C]3.29[/C][/ROW]
[ROW][C]4[/C][C]8.91991666666667[/C][C]0.695551770288535[/C][C]2.222[/C][/ROW]
[ROW][C]5[/C][C]8.4955[/C][C]0.756642043385234[/C][C]2.622[/C][/ROW]
[ROW][C]6[/C][C]8.6065[/C][C]0.981102024163737[/C][C]2.895[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61049&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
18.741916666666671.094680813448994.275
28.620583333333330.6680329956920792.366
38.80350.8818782125771013.29
48.919916666666670.6955517702885352.222
58.49550.7566420433852342.622
68.60650.9811020241637372.895






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.78495131338313
beta0.00705488938384951
S.D.0.552461103377964
T-STAT0.0127699295764229
p-value0.990422878179768

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.78495131338313 \tabularnewline
beta & 0.00705488938384951 \tabularnewline
S.D. & 0.552461103377964 \tabularnewline
T-STAT & 0.0127699295764229 \tabularnewline
p-value & 0.990422878179768 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61049&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.78495131338313[/C][/ROW]
[ROW][C]beta[/C][C]0.00705488938384951[/C][/ROW]
[ROW][C]S.D.[/C][C]0.552461103377964[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0127699295764229[/C][/ROW]
[ROW][C]p-value[/C][C]0.990422878179768[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61049&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61049&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)
alpha0.78495131338313
beta0.00705488938384951
S.D.0.552461103377964
T-STAT0.0127699295764229
p-value0.990422878179768






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.221030209083125
beta0.0174553372871013
S.D.5.60636533302789
T-STAT0.00311348552051531
p-value0.997664890575458
Lambda0.982544662712899

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.221030209083125 \tabularnewline
beta & 0.0174553372871013 \tabularnewline
S.D. & 5.60636533302789 \tabularnewline
T-STAT & 0.00311348552051531 \tabularnewline
p-value & 0.997664890575458 \tabularnewline
Lambda & 0.982544662712899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61049&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.221030209083125[/C][/ROW]
[ROW][C]beta[/C][C]0.0174553372871013[/C][/ROW]
[ROW][C]S.D.[/C][C]5.60636533302789[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.00311348552051531[/C][/ROW]
[ROW][C]p-value[/C][C]0.997664890575458[/C][/ROW]
[ROW][C]Lambda[/C][C]0.982544662712899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61049&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61049&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)
alpha-0.221030209083125
beta0.0174553372871013
S.D.5.60636533302789
T-STAT0.00311348552051531
p-value0.997664890575458
Lambda0.982544662712899


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')