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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 computationThu, 22 Nov 2007 14:52:56 -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/2007/Nov/22/t1195767896g4cg23vqg5ebji0.htm/, Retrieved Fri, 03 May 2024 03:38:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6107, Retrieved Fri, 03 May 2024 03:38:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ1, totaal
Estimated Impact194

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] [Q1, totaal] [2007-11-22 21:52:56] [234bcf6fb77cd83fa17f2489a043102b] [Current]
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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
133,5
102,1
102,4

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6107&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6107&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1103.67511.959258490239436.9
299.816666666666710.041263351639119.9
396.56666666666679.435458589166663.7
4103.71666666666710.776053699445520.1
5105.53333333333312.933911264813231.2
6112.98333333333314.069362803516424.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 103.675 & 11.9592584902394 & 36.9 \tabularnewline
2 & 99.8166666666667 & 10.0412633516391 & 19.9 \tabularnewline
3 & 96.5666666666667 & 9.43545858916666 & 3.7 \tabularnewline
4 & 103.716666666667 & 10.7760536994455 & 20.1 \tabularnewline
5 & 105.533333333333 & 12.9339112648132 & 31.2 \tabularnewline
6 & 112.983333333333 & 14.0693628035164 & 24.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6107&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]36.9[/C][/ROW]
[ROW][C]2[/C][C]99.8166666666667[/C][C]10.0412633516391[/C][C]19.9[/C][/ROW]
[ROW][C]3[/C][C]96.5666666666667[/C][C]9.43545858916666[/C][C]3.7[/C][/ROW]
[ROW][C]4[/C][C]103.716666666667[/C][C]10.7760536994455[/C][C]20.1[/C][/ROW]
[ROW][C]5[/C][C]105.533333333333[/C][C]12.9339112648132[/C][C]31.2[/C][/ROW]
[ROW][C]6[/C][C]112.983333333333[/C][C]14.0693628035164[/C][C]24.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6107&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
1103.67511.959258490239436.9
299.816666666666710.041263351639119.9
396.56666666666679.435458589166663.7
4103.71666666666710.776053699445520.1
5105.53333333333312.933911264813231.2
6112.98333333333314.069362803516424.3






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-19.7083485225288
beta0.301250055843042
S.D.0.0517043639783743
T-STAT5.82639515629747
p-value0.00432251483357204

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -19.7083485225288 \tabularnewline
beta & 0.301250055843042 \tabularnewline
S.D. & 0.0517043639783743 \tabularnewline
T-STAT & 5.82639515629747 \tabularnewline
p-value & 0.00432251483357204 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6107&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-19.7083485225288[/C][/ROW]
[ROW][C]beta[/C][C]0.301250055843042[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0517043639783743[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.82639515629747[/C][/ROW]
[ROW][C]p-value[/C][C]0.00432251483357204[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6107&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6107&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-19.7083485225288
beta0.301250055843042
S.D.0.0517043639783743
T-STAT5.82639515629747
p-value0.00432251483357204






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-10.1784203397961
beta2.71827881750915
S.D.0.472735042230533
T-STAT5.7501106850115
p-value0.0045350989781328
Lambda-1.71827881750915

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -10.1784203397961 \tabularnewline
beta & 2.71827881750915 \tabularnewline
S.D. & 0.472735042230533 \tabularnewline
T-STAT & 5.7501106850115 \tabularnewline
p-value & 0.0045350989781328 \tabularnewline
Lambda & -1.71827881750915 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6107&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-10.1784203397961[/C][/ROW]
[ROW][C]beta[/C][C]2.71827881750915[/C][/ROW]
[ROW][C]S.D.[/C][C]0.472735042230533[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.7501106850115[/C][/ROW]
[ROW][C]p-value[/C][C]0.0045350989781328[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.71827881750915[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6107&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6107&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-10.1784203397961
beta2.71827881750915
S.D.0.472735042230533
T-STAT5.7501106850115
p-value0.0045350989781328
Lambda-1.71827881750915


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')