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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, 28 Nov 2011 09:46:30 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/28/t132249170041nd1tnh8tiglxz.htm/, Retrieved Thu, 25 Apr 2024 23:39:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147775, Retrieved Thu, 25 Apr 2024 23:39:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W83
Estimated Impact104

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] [Opdracht 8 oefeni...] [2011-11-28 14:46:30] [5c7e349a99f3f4c38d746f616922f776] [Current]
- R P     [Standard Deviation-Mean Plot] [Opdracht 8 verbet...] [2011-12-05 11:58:03] [78ad7246c13d73188e9e2bc44b7acf73]
- RMPD      [Classical Decomposition] [Opdracht 9 oefeni...] [2011-12-05 18:07:32] [78ad7246c13d73188e9e2bc44b7acf73]
- RMPD      [Classical Decomposition] [Opdracht 9 oefeni...] [2011-12-05 18:07:32] [78ad7246c13d73188e9e2bc44b7acf73]
- RMP       [Classical Decomposition] [Opdracht 9 oefeni...] [2011-12-05 18:13:43] [78ad7246c13d73188e9e2bc44b7acf73]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6
6
5
3
2
3
3
2
0
4
4
5
6
6
5
5
3
5
5
5
3
6
6
4
6
5
4
5
5
4
3
2
3
2
-1
0
-2
1
-2
-2
-2
-6
-4
-2
0
-5
-4
-5
-1
-2
-4
-1
1
1
-2
1
1
3
3
1
1
0
2
2
-1
1
0
1
1
3
2
0

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'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147775&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147775&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147775&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
151.41421356237313
22.50.5773502691896261
33.252.217355782608355
45.50.5773502691896261
54.512
64.751.53
750.8164965809277262
83.51.290994448735813
911.825741858350554
10-1.251.53
11-3.51.914854215512684
12-3.52.380476142847625
13-21.41421356237313
140.251.53
1521.154700538379252
161.250.9574271077563382
170.250.9574271077563382
181.51.290994448735813

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 5 & 1.4142135623731 & 3 \tabularnewline
2 & 2.5 & 0.577350269189626 & 1 \tabularnewline
3 & 3.25 & 2.21735578260835 & 5 \tabularnewline
4 & 5.5 & 0.577350269189626 & 1 \tabularnewline
5 & 4.5 & 1 & 2 \tabularnewline
6 & 4.75 & 1.5 & 3 \tabularnewline
7 & 5 & 0.816496580927726 & 2 \tabularnewline
8 & 3.5 & 1.29099444873581 & 3 \tabularnewline
9 & 1 & 1.82574185835055 & 4 \tabularnewline
10 & -1.25 & 1.5 & 3 \tabularnewline
11 & -3.5 & 1.91485421551268 & 4 \tabularnewline
12 & -3.5 & 2.38047614284762 & 5 \tabularnewline
13 & -2 & 1.4142135623731 & 3 \tabularnewline
14 & 0.25 & 1.5 & 3 \tabularnewline
15 & 2 & 1.15470053837925 & 2 \tabularnewline
16 & 1.25 & 0.957427107756338 & 2 \tabularnewline
17 & 0.25 & 0.957427107756338 & 2 \tabularnewline
18 & 1.5 & 1.29099444873581 & 3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147775&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]5[/C][C]1.4142135623731[/C][C]3[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]0.577350269189626[/C][C]1[/C][/ROW]
[ROW][C]3[/C][C]3.25[/C][C]2.21735578260835[/C][C]5[/C][/ROW]
[ROW][C]4[/C][C]5.5[/C][C]0.577350269189626[/C][C]1[/C][/ROW]
[ROW][C]5[/C][C]4.5[/C][C]1[/C][C]2[/C][/ROW]
[ROW][C]6[/C][C]4.75[/C][C]1.5[/C][C]3[/C][/ROW]
[ROW][C]7[/C][C]5[/C][C]0.816496580927726[/C][C]2[/C][/ROW]
[ROW][C]8[/C][C]3.5[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]1.82574185835055[/C][C]4[/C][/ROW]
[ROW][C]10[/C][C]-1.25[/C][C]1.5[/C][C]3[/C][/ROW]
[ROW][C]11[/C][C]-3.5[/C][C]1.91485421551268[/C][C]4[/C][/ROW]
[ROW][C]12[/C][C]-3.5[/C][C]2.38047614284762[/C][C]5[/C][/ROW]
[ROW][C]13[/C][C]-2[/C][C]1.4142135623731[/C][C]3[/C][/ROW]
[ROW][C]14[/C][C]0.25[/C][C]1.5[/C][C]3[/C][/ROW]
[ROW][C]15[/C][C]2[/C][C]1.15470053837925[/C][C]2[/C][/ROW]
[ROW][C]16[/C][C]1.25[/C][C]0.957427107756338[/C][C]2[/C][/ROW]
[ROW][C]17[/C][C]0.25[/C][C]0.957427107756338[/C][C]2[/C][/ROW]
[ROW][C]18[/C][C]1.5[/C][C]1.29099444873581[/C][C]3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147775&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147775&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
151.41421356237313
22.50.5773502691896261
33.252.217355782608355
45.50.5773502691896261
54.512
64.751.53
750.8164965809277262
83.51.290994448735813
911.825741858350554
10-1.251.53
11-3.51.914854215512684
12-3.52.380476142847625
13-21.41421356237313
140.251.53
1521.154700538379252
161.250.9574271077563382
170.250.9574271077563382
181.51.290994448735813






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.50548610043657
beta-0.0936384637707438
S.D.0.03736413171759
T-STAT-2.50610570796863
p-value0.0233851052610155

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.50548610043657 \tabularnewline
beta & -0.0936384637707438 \tabularnewline
S.D. & 0.03736413171759 \tabularnewline
T-STAT & -2.50610570796863 \tabularnewline
p-value & 0.0233851052610155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147775&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.50548610043657[/C][/ROW]
[ROW][C]beta[/C][C]-0.0936384637707438[/C][/ROW]
[ROW][C]S.D.[/C][C]0.03736413171759[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.50610570796863[/C][/ROW]
[ROW][C]p-value[/C][C]0.0233851052610155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147775&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147775&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)
alpha1.50548610043657
beta-0.0936384637707438
S.D.0.03736413171759
T-STAT-2.50610570796863
p-value0.0233851052610155






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha0.175710212245182
beta-0.0645396017213361
S.D.0.107183094000587
T-STAT-0.602143484689692
p-value0.558284933125048
Lambda1.06453960172134

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.175710212245182 \tabularnewline
beta & -0.0645396017213361 \tabularnewline
S.D. & 0.107183094000587 \tabularnewline
T-STAT & -0.602143484689692 \tabularnewline
p-value & 0.558284933125048 \tabularnewline
Lambda & 1.06453960172134 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147775&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.175710212245182[/C][/ROW]
[ROW][C]beta[/C][C]-0.0645396017213361[/C][/ROW]
[ROW][C]S.D.[/C][C]0.107183094000587[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.602143484689692[/C][/ROW]
[ROW][C]p-value[/C][C]0.558284933125048[/C][/ROW]
[ROW][C]Lambda[/C][C]1.06453960172134[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147775&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147775&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)
alpha0.175710212245182
beta-0.0645396017213361
S.D.0.107183094000587
T-STAT-0.602143484689692
p-value0.558284933125048
Lambda1.06453960172134


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')