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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, 06 Dec 2010 11:37:42 +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/2010/Dec/06/t1291635346v0j30cmsvt2o4d7.htm/, Retrieved Mon, 29 Apr 2024 03:44:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105556, Retrieved Mon, 29 Apr 2024 03:44:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact155

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] [spreidings-gemidd...] [2010-12-06 11:37:42] [6828a15931dcaf58ef367cb5857a54a7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96,92
99,06
99,65
99,82
99,99
100,33
99,31
101,1
101,1
100,93
100,85
100,93
99,6
101,88
101,81
102,38
102,74
102,82
101,72
103,47
102,98
102,68
102,9
103,03
101,29
103,69
103,68
104,2
104,08
104,16
103,05
104,66
104,46
104,95
105,85
106,23
104,86
107,44
108,23
108,45
109,39
110,15
109,13
110,28
110,17
109,99
109,26
109,11
107,06
109,53
108,92
109,24
109,12
109
107,23
109,49
109,04
109,02
109,23
109,46

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105556&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105556&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105556&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
198.86251.335324554805562.89999999999999
2100.18250.744283772047551.78999999999999
3100.95250.1053169818531950.25
4101.41751.237965400701222.78
5102.68750.723112485486641.75
6102.89750.1545692940614860.349999999999994
7103.2151.306101068064792.91000000000000
8103.98750.6756416703154611.61
9105.37250.811269581170981.77000000000001
10107.2451.648079690629883.59
11109.73750.5639961583793551.15000000000001
12109.63250.525507691031571.06000000000000
13108.68751.113234776076762.47
14108.711.008464178838292.25999999999999
15109.18750.2048373338367110.439999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 98.8625 & 1.33532455480556 & 2.89999999999999 \tabularnewline
2 & 100.1825 & 0.74428377204755 & 1.78999999999999 \tabularnewline
3 & 100.9525 & 0.105316981853195 & 0.25 \tabularnewline
4 & 101.4175 & 1.23796540070122 & 2.78 \tabularnewline
5 & 102.6875 & 0.72311248548664 & 1.75 \tabularnewline
6 & 102.8975 & 0.154569294061486 & 0.349999999999994 \tabularnewline
7 & 103.215 & 1.30610106806479 & 2.91000000000000 \tabularnewline
8 & 103.9875 & 0.675641670315461 & 1.61 \tabularnewline
9 & 105.3725 & 0.81126958117098 & 1.77000000000001 \tabularnewline
10 & 107.245 & 1.64807969062988 & 3.59 \tabularnewline
11 & 109.7375 & 0.563996158379355 & 1.15000000000001 \tabularnewline
12 & 109.6325 & 0.52550769103157 & 1.06000000000000 \tabularnewline
13 & 108.6875 & 1.11323477607676 & 2.47 \tabularnewline
14 & 108.71 & 1.00846417883829 & 2.25999999999999 \tabularnewline
15 & 109.1875 & 0.204837333836711 & 0.439999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105556&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]98.8625[/C][C]1.33532455480556[/C][C]2.89999999999999[/C][/ROW]
[ROW][C]2[/C][C]100.1825[/C][C]0.74428377204755[/C][C]1.78999999999999[/C][/ROW]
[ROW][C]3[/C][C]100.9525[/C][C]0.105316981853195[/C][C]0.25[/C][/ROW]
[ROW][C]4[/C][C]101.4175[/C][C]1.23796540070122[/C][C]2.78[/C][/ROW]
[ROW][C]5[/C][C]102.6875[/C][C]0.72311248548664[/C][C]1.75[/C][/ROW]
[ROW][C]6[/C][C]102.8975[/C][C]0.154569294061486[/C][C]0.349999999999994[/C][/ROW]
[ROW][C]7[/C][C]103.215[/C][C]1.30610106806479[/C][C]2.91000000000000[/C][/ROW]
[ROW][C]8[/C][C]103.9875[/C][C]0.675641670315461[/C][C]1.61[/C][/ROW]
[ROW][C]9[/C][C]105.3725[/C][C]0.81126958117098[/C][C]1.77000000000001[/C][/ROW]
[ROW][C]10[/C][C]107.245[/C][C]1.64807969062988[/C][C]3.59[/C][/ROW]
[ROW][C]11[/C][C]109.7375[/C][C]0.563996158379355[/C][C]1.15000000000001[/C][/ROW]
[ROW][C]12[/C][C]109.6325[/C][C]0.52550769103157[/C][C]1.06000000000000[/C][/ROW]
[ROW][C]13[/C][C]108.6875[/C][C]1.11323477607676[/C][C]2.47[/C][/ROW]
[ROW][C]14[/C][C]108.71[/C][C]1.00846417883829[/C][C]2.25999999999999[/C][/ROW]
[ROW][C]15[/C][C]109.1875[/C][C]0.204837333836711[/C][C]0.439999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105556&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105556&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
198.86251.335324554805562.89999999999999
2100.18250.744283772047551.78999999999999
3100.95250.1053169818531950.25
4101.41751.237965400701222.78
5102.68750.723112485486641.75
6102.89750.1545692940614860.349999999999994
7103.2151.306101068064792.91000000000000
8103.98750.6756416703154611.61
9105.37250.811269581170981.77000000000001
10107.2451.648079690629883.59
11109.73750.5639961583793551.15000000000001
12109.63250.525507691031571.06000000000000
13108.68751.113234776076762.47
14108.711.008464178838292.25999999999999
15109.18750.2048373338367110.439999999999998






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.89178316388280
beta-0.0103123732389837
S.D.0.0340589203240933
T-STAT-0.302780391769751
p-value0.766847715131115

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.89178316388280 \tabularnewline
beta & -0.0103123732389837 \tabularnewline
S.D. & 0.0340589203240933 \tabularnewline
T-STAT & -0.302780391769751 \tabularnewline
p-value & 0.766847715131115 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105556&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.89178316388280[/C][/ROW]
[ROW][C]beta[/C][C]-0.0103123732389837[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0340589203240933[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.302780391769751[/C][/ROW]
[ROW][C]p-value[/C][C]0.766847715131115[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105556&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105556&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)
alpha1.89178316388280
beta-0.0103123732389837
S.D.0.0340589203240933
T-STAT-0.302780391769751
p-value0.766847715131115






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.23021863428775
beta0.382606539949857
S.D.6.40748355350967
T-STAT0.0597124497869816
p-value0.95329283915915
Lambda0.617393460050143

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.23021863428775 \tabularnewline
beta & 0.382606539949857 \tabularnewline
S.D. & 6.40748355350967 \tabularnewline
T-STAT & 0.0597124497869816 \tabularnewline
p-value & 0.95329283915915 \tabularnewline
Lambda & 0.617393460050143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105556&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.23021863428775[/C][/ROW]
[ROW][C]beta[/C][C]0.382606539949857[/C][/ROW]
[ROW][C]S.D.[/C][C]6.40748355350967[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.0597124497869816[/C][/ROW]
[ROW][C]p-value[/C][C]0.95329283915915[/C][/ROW]
[ROW][C]Lambda[/C][C]0.617393460050143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105556&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105556&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-2.23021863428775
beta0.382606539949857
S.D.6.40748355350967
T-STAT0.0597124497869816
p-value0.95329283915915
Lambda0.617393460050143


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')