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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 computationFri, 27 Nov 2009 05:47:40 -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/27/t125932638496c7t3ejyxskj4j.htm/, Retrieved Mon, 29 Apr 2024 05:45:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60676, Retrieved Mon, 29 Apr 2024 05:45:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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]
-    D          [Standard Deviation-Mean Plot] [] [2009-11-27 12:47:40] [c588bf81b9040ce04d6292d0d83341a9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
31
26
18
26
26
27
22
24
31
23
31
37
42
43
48
46
45
52
46
53
47
43
44
48
48
51
57
50
38
31
31
37
26
36
41
44
50
49
48
50
52
53
59
53
59
61
62
54
62
63
63
71
65
65
61
59
53
55
39
36
29
31
30
23
19
14
3
6
13
3
6
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'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=60676&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=60676&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60676&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
126.83333333333335.060243137049919
246.41666666666673.4498572653829011
340.83333333333339.3889038311996331
454.16666666666674.8772819057215514
557.666666666666710.534215536512335
614.7511.426643506217531

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 26.8333333333333 & 5.0602431370499 & 19 \tabularnewline
2 & 46.4166666666667 & 3.44985726538290 & 11 \tabularnewline
3 & 40.8333333333333 & 9.38890383119963 & 31 \tabularnewline
4 & 54.1666666666667 & 4.87728190572155 & 14 \tabularnewline
5 & 57.6666666666667 & 10.5342155365123 & 35 \tabularnewline
6 & 14.75 & 11.4266435062175 & 31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60676&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]26.8333333333333[/C][C]5.0602431370499[/C][C]19[/C][/ROW]
[ROW][C]2[/C][C]46.4166666666667[/C][C]3.44985726538290[/C][C]11[/C][/ROW]
[ROW][C]3[/C][C]40.8333333333333[/C][C]9.38890383119963[/C][C]31[/C][/ROW]
[ROW][C]4[/C][C]54.1666666666667[/C][C]4.87728190572155[/C][C]14[/C][/ROW]
[ROW][C]5[/C][C]57.6666666666667[/C][C]10.5342155365123[/C][C]35[/C][/ROW]
[ROW][C]6[/C][C]14.75[/C][C]11.4266435062175[/C][C]31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60676&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60676&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
126.83333333333335.060243137049919
246.41666666666673.4498572653829011
340.83333333333339.3889038311996331
454.16666666666674.8772819057215514
557.666666666666710.534215536512335
614.7511.426643506217531






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha9.6580818407175
beta-0.0548947889011963
S.D.0.0987845695380115
T-STAT-0.555702061140968
p-value0.608029060783932

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 9.6580818407175 \tabularnewline
beta & -0.0548947889011963 \tabularnewline
S.D. & 0.0987845695380115 \tabularnewline
T-STAT & -0.555702061140968 \tabularnewline
p-value & 0.608029060783932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60676&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.6580818407175[/C][/ROW]
[ROW][C]beta[/C][C]-0.0548947889011963[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0987845695380115[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.555702061140968[/C][/ROW]
[ROW][C]p-value[/C][C]0.608029060783932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60676&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60676&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)
alpha9.6580818407175
beta-0.0548947889011963
S.D.0.0987845695380115
T-STAT-0.555702061140968
p-value0.608029060783932






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.07633403216542
beta-0.323690923944216
S.D.0.447389979520240
T-STAT-0.723509552653206
p-value0.509413411285294
Lambda1.32369092394422

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.07633403216542 \tabularnewline
beta & -0.323690923944216 \tabularnewline
S.D. & 0.447389979520240 \tabularnewline
T-STAT & -0.723509552653206 \tabularnewline
p-value & 0.509413411285294 \tabularnewline
Lambda & 1.32369092394422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60676&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.07633403216542[/C][/ROW]
[ROW][C]beta[/C][C]-0.323690923944216[/C][/ROW]
[ROW][C]S.D.[/C][C]0.447389979520240[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.723509552653206[/C][/ROW]
[ROW][C]p-value[/C][C]0.509413411285294[/C][/ROW]
[ROW][C]Lambda[/C][C]1.32369092394422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60676&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60676&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)
alpha3.07633403216542
beta-0.323690923944216
S.D.0.447389979520240
T-STAT-0.723509552653206
p-value0.509413411285294
Lambda1.32369092394422


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')