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Description of Statistical Computation

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 computationWed, 25 Nov 2009 11:26:43 -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/25/t1259173647kw309cnckoyk7i2.htm/, Retrieved Tue, 07 May 2024 21:21:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59541, Retrieved Tue, 07 May 2024 21:21:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsws8l10
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
F    D          [Standard Deviation-Mean Plot] [] [2009-11-25 18:26:43] [42ed2e0ab6f351a3dce7cf3f388e378d] [Current]
Feedback Forum
2009-12-04 13:32:23 [Angelo Stuer] [reply] 
conclusie: Je bekomt een p-waarde van 28%. Dit is niet veel maar genoeg om de nulhypothese te aanvaarden. Dit betekent dat het niet nodig is om de lambda-waarde te veranderen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,3
6,1
6,1
6,3
6,3
6
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
8,1
8,2
8,3
8,2
8
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
8,2
8,1
8,1
8
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
7,2
7,3
7,1
6,8
6,4
6,1
6,5
7,7
7,9
7,5
6,9
6,6
6,9
7,7

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=59541&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=59541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59541&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
16.591666666666670.6022055422789761.6
27.5250.4535215741084631.4
38.1750.32787192621511
48.391666666666670.7128155866744642.1
58.433333333333330.2461829819586650.799999999999999
68.250.3030151511363440.799999999999999
77.483333333333330.4174235549683611
86.9750.5462683323322811.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6.59166666666667 & 0.602205542278976 & 1.6 \tabularnewline
2 & 7.525 & 0.453521574108463 & 1.4 \tabularnewline
3 & 8.175 & 0.3278719262151 & 1 \tabularnewline
4 & 8.39166666666667 & 0.712815586674464 & 2.1 \tabularnewline
5 & 8.43333333333333 & 0.246182981958665 & 0.799999999999999 \tabularnewline
6 & 8.25 & 0.303015151136344 & 0.799999999999999 \tabularnewline
7 & 7.48333333333333 & 0.417423554968361 & 1 \tabularnewline
8 & 6.975 & 0.546268332332281 & 1.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59541&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]6.59166666666667[/C][C]0.602205542278976[/C][C]1.6[/C][/ROW]
[ROW][C]2[/C][C]7.525[/C][C]0.453521574108463[/C][C]1.4[/C][/ROW]
[ROW][C]3[/C][C]8.175[/C][C]0.3278719262151[/C][C]1[/C][/ROW]
[ROW][C]4[/C][C]8.39166666666667[/C][C]0.712815586674464[/C][C]2.1[/C][/ROW]
[ROW][C]5[/C][C]8.43333333333333[/C][C]0.246182981958665[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]6[/C][C]8.25[/C][C]0.303015151136344[/C][C]0.799999999999999[/C][/ROW]
[ROW][C]7[/C][C]7.48333333333333[/C][C]0.417423554968361[/C][C]1[/C][/ROW]
[ROW][C]8[/C][C]6.975[/C][C]0.546268332332281[/C][C]1.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59541&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
16.591666666666670.6022055422789761.6
27.5250.4535215741084631.4
38.1750.32787192621511
48.391666666666670.7128155866744642.1
58.433333333333330.2461829819586650.799999999999999
68.250.3030151511363440.799999999999999
77.483333333333330.4174235549683611
86.9750.5462683323322811.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.22830760454754
beta-0.100560552959282
S.D.0.085140854489492
T-STAT-1.18110810094927
p-value0.282251310709737

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.22830760454754 \tabularnewline
beta & -0.100560552959282 \tabularnewline
S.D. & 0.085140854489492 \tabularnewline
T-STAT & -1.18110810094927 \tabularnewline
p-value & 0.282251310709737 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59541&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.22830760454754[/C][/ROW]
[ROW][C]beta[/C][C]-0.100560552959282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.085140854489492[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.18110810094927[/C][/ROW]
[ROW][C]p-value[/C][C]0.282251310709737[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59541&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59541&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)
alpha1.22830760454754
beta-0.100560552959282
S.D.0.085140854489492
T-STAT-1.18110810094927
p-value0.282251310709737






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.41651250821033
beta-2.09173670016648
S.D.1.37933551347403
T-STAT-1.51648143597650
p-value0.180185237787372
Lambda3.09173670016648

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.41651250821033 \tabularnewline
beta & -2.09173670016648 \tabularnewline
S.D. & 1.37933551347403 \tabularnewline
T-STAT & -1.51648143597650 \tabularnewline
p-value & 0.180185237787372 \tabularnewline
Lambda & 3.09173670016648 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59541&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.41651250821033[/C][/ROW]
[ROW][C]beta[/C][C]-2.09173670016648[/C][/ROW]
[ROW][C]S.D.[/C][C]1.37933551347403[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.51648143597650[/C][/ROW]
[ROW][C]p-value[/C][C]0.180185237787372[/C][/ROW]
[ROW][C]Lambda[/C][C]3.09173670016648[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59541&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59541&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)
alpha3.41651250821033
beta-2.09173670016648
S.D.1.37933551347403
T-STAT-1.51648143597650
p-value0.180185237787372
Lambda3.09173670016648


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')