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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 computationTue, 09 Dec 2008 10:36:29 -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/2008/Dec/09/t1228844264qod65n68tid0f13.htm/, Retrieved Sat, 25 May 2024 09:48:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31619, Retrieved Sat, 25 May 2024 09:48:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Gilliam Schoorel] [2008-12-07 20:50:54] [a9b974cca921a7a5a84c6ce01f3dc8c2]
F RMPD      [Standard Deviation-Mean Plot] [] [2008-12-09 17:36:29] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-13 22:42:28 [Li Tang Hu] [reply] 
pwaarde is te groot, dus gaan we lambda gelijk stellen aan 1 in verdere berekeningen

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106.7
110.2
125.9
100.1
106.4
114.8
81.3
87
104.2
108
105
94.5
92
95.9
108.8
103.4
102.1
110.1
83.2
82.7
106.8
113.7
102.5
96.6
92.1
95.6
102.3
98.6
98.2
104.5
84
73.8
103.9
106
97.2
102.6
89
93.8
116.7
106.8
98.5
118.7
90
91.9
113.3
113.1
104.1
108.7
96.7
101
116.9
105.8
99
129.4
83
88.9
115.9
104.2
113.4
112.2
100.8
107.3
126.6
102.9
117.9
128.8
87.5
93.8
122.7
126.2
124.6
116.7
115.2
111.1
129.9
113.3
118.5
137.9
103.6
101.7
127.4
137.5
128.3
118.2
117.1
124.2
126
132.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31619&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31619&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31619&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1103.67511.959258490239444.6
299.816666666666710.041263351639131
396.56666666666679.4354585891666632.2
4103.71666666666710.776053699445529.7
5105.53333333333312.933911264813246.4
6112.98333333333314.069362803516441.3
7120.21666666666712.076410765194136.2

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.675 & 11.9592584902394 & 44.6 \tabularnewline
2 & 99.8166666666667 & 10.0412633516391 & 31 \tabularnewline
3 & 96.5666666666667 & 9.43545858916666 & 32.2 \tabularnewline
4 & 103.716666666667 & 10.7760536994455 & 29.7 \tabularnewline
5 & 105.533333333333 & 12.9339112648132 & 46.4 \tabularnewline
6 & 112.983333333333 & 14.0693628035164 & 41.3 \tabularnewline
7 & 120.216666666667 & 12.0764107651941 & 36.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31619&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]103.675[/C][C]11.9592584902394[/C][C]44.6[/C][/ROW]
[ROW][C]2[/C][C]99.8166666666667[/C][C]10.0412633516391[/C][C]31[/C][/ROW]
[ROW][C]3[/C][C]96.5666666666667[/C][C]9.43545858916666[/C][C]32.2[/C][/ROW]
[ROW][C]4[/C][C]103.716666666667[/C][C]10.7760536994455[/C][C]29.7[/C][/ROW]
[ROW][C]5[/C][C]105.533333333333[/C][C]12.9339112648132[/C][C]46.4[/C][/ROW]
[ROW][C]6[/C][C]112.983333333333[/C][C]14.0693628035164[/C][C]41.3[/C][/ROW]
[ROW][C]7[/C][C]120.216666666667[/C][C]12.0764107651941[/C][C]36.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31619&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31619&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
1103.67511.959258490239444.6
299.816666666666710.041263351639131
396.56666666666679.4354585891666632.2
4103.71666666666710.776053699445529.7
5105.53333333333312.933911264813246.4
6112.98333333333314.069362803516441.3
7120.21666666666712.076410765194136.2






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-3.2493417579027
beta0.140115749007531
S.D.0.0656888159041583
T-STAT2.13302290624272
p-value0.0860740702059154

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -3.2493417579027 \tabularnewline
beta & 0.140115749007531 \tabularnewline
S.D. & 0.0656888159041583 \tabularnewline
T-STAT & 2.13302290624272 \tabularnewline
p-value & 0.0860740702059154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31619&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.2493417579027[/C][/ROW]
[ROW][C]beta[/C][C]0.140115749007531[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0656888159041583[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13302290624272[/C][/ROW]
[ROW][C]p-value[/C][C]0.0860740702059154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31619&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31619&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)
alpha-3.2493417579027
beta0.140115749007531
S.D.0.0656888159041583
T-STAT2.13302290624272
p-value0.0860740702059154






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.97254199620903
beta1.37634327607465
S.D.0.587853558114105
T-STAT2.34130296070692
p-value0.0662727066828365
Lambda-0.376343276074651

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.97254199620903 \tabularnewline
beta & 1.37634327607465 \tabularnewline
S.D. & 0.587853558114105 \tabularnewline
T-STAT & 2.34130296070692 \tabularnewline
p-value & 0.0662727066828365 \tabularnewline
Lambda & -0.376343276074651 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31619&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.97254199620903[/C][/ROW]
[ROW][C]beta[/C][C]1.37634327607465[/C][/ROW]
[ROW][C]S.D.[/C][C]0.587853558114105[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.34130296070692[/C][/ROW]
[ROW][C]p-value[/C][C]0.0662727066828365[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.376343276074651[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31619&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31619&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-3.97254199620903
beta1.37634327607465
S.D.0.587853558114105
T-STAT2.34130296070692
p-value0.0662727066828365
Lambda-0.376343276074651


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')