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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 computationSat, 28 Nov 2009 02:24:20 -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/28/t1259400350w2eohs59n2m7pan.htm/, Retrieved Fri, 03 May 2024 11:25:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61391, Retrieved Fri, 03 May 2024 11:25:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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]
-   PD          [Standard Deviation-Mean Plot] [ws8: heteroskedas...] [2009-11-28 09:24:20] [a315839f8c359622c3a1e6ed387dd5cd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566

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=61391&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=61391&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61391&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
123002.754411.5029004761113914
223855.08333333336758.4977144377722631
322326.66666666675909.3201475347921258
422846.83333333337212.8372028731925139
523530.255325.4125085634118828

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 23002.75 & 4411.50290047611 & 13914 \tabularnewline
2 & 23855.0833333333 & 6758.49771443777 & 22631 \tabularnewline
3 & 22326.6666666667 & 5909.32014753479 & 21258 \tabularnewline
4 & 22846.8333333333 & 7212.83720287319 & 25139 \tabularnewline
5 & 23530.25 & 5325.41250856341 & 18828 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61391&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]23002.75[/C][C]4411.50290047611[/C][C]13914[/C][/ROW]
[ROW][C]2[/C][C]23855.0833333333[/C][C]6758.49771443777[/C][C]22631[/C][/ROW]
[ROW][C]3[/C][C]22326.6666666667[/C][C]5909.32014753479[/C][C]21258[/C][/ROW]
[ROW][C]4[/C][C]22846.8333333333[/C][C]7212.83720287319[/C][C]25139[/C][/ROW]
[ROW][C]5[/C][C]23530.25[/C][C]5325.41250856341[/C][C]18828[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61391&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61391&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
123002.754411.5029004761113914
223855.08333333336758.4977144377722631
322326.66666666675909.3201475347921258
422846.83333333337212.8372028731925139
523530.255325.4125085634118828






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha2605.12417353473
beta0.143576689827386
S.D.1.07827152334306
T-STAT0.133154485414066
p-value0.902501066130464

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2605.12417353473 \tabularnewline
beta & 0.143576689827386 \tabularnewline
S.D. & 1.07827152334306 \tabularnewline
T-STAT & 0.133154485414066 \tabularnewline
p-value & 0.902501066130464 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61391&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2605.12417353473[/C][/ROW]
[ROW][C]beta[/C][C]0.143576689827386[/C][/ROW]
[ROW][C]S.D.[/C][C]1.07827152334306[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.133154485414066[/C][/ROW]
[ROW][C]p-value[/C][C]0.902501066130464[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61391&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61391&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)
alpha2605.12417353473
beta0.143576689827386
S.D.1.07827152334306
T-STAT0.133154485414066
p-value0.902501066130464






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.21451358284712
beta0.543123111312713
S.D.4.35989874388245
T-STAT0.124572413998098
p-value0.908740501577105
Lambda0.456876888687287

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.21451358284712 \tabularnewline
beta & 0.543123111312713 \tabularnewline
S.D. & 4.35989874388245 \tabularnewline
T-STAT & 0.124572413998098 \tabularnewline
p-value & 0.908740501577105 \tabularnewline
Lambda & 0.456876888687287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61391&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.21451358284712[/C][/ROW]
[ROW][C]beta[/C][C]0.543123111312713[/C][/ROW]
[ROW][C]S.D.[/C][C]4.35989874388245[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.124572413998098[/C][/ROW]
[ROW][C]p-value[/C][C]0.908740501577105[/C][/ROW]
[ROW][C]Lambda[/C][C]0.456876888687287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61391&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61391&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)
alpha3.21451358284712
beta0.543123111312713
S.D.4.35989874388245
T-STAT0.124572413998098
p-value0.908740501577105
Lambda0.456876888687287


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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')