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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, 06 Dec 2007 06:33:22 -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/Dec/06/t11969472462isox5tbxnbgbgk.htm/, Retrieved Fri, 03 May 2024 09:01:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2598, Retrieved Fri, 03 May 2024 09:01:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInne Devriendt
Estimated Impact184

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] [Vraag 1 workshop ...] [2007-12-06 13:33:22] [011cc8cdd02d5893b5258ac3f5e21d83] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,6
1,59
1,6
1,6
1,59
1,59
1,58
1,59
1,59
1,58
1,58
1,58
1,57
1,57
1,57
1,57
1,58
1,58
1,57
1,58
1,57
1,57
1,57
1,57
1,57
1,57
1,59
1,6
1,6
1,6
1,6
1,61
1,61
1,62
1,62
1,62
1,62
1,62
1,62
1,61
1,59
1,58
1,56
1,56
1,54
1,55
1,56
1,57
1,58
1,59
1,6
1,6
1,61
1,61
1,62
1,61
1,6
1,6
1,6
1,61
1,62
1,63
1,63
1,66
1,66
1,66
1,65
1,65
1,64
1,64
1,65
1,64

Tables (Output of Computation)





Summary of compuational 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 compuational 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=2598&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]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=2598&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2598&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.589166666666670.00792961461098760.03
21.57250.004522670168666460.01
31.600833333333330.01729862492345630.05
41.581666666666670.02949062511539850.05
51.60250.01055289706022170.04
61.644166666666670.01311372170551500.0799999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.58916666666667 & 0.0079296146109876 & 0.03 \tabularnewline
2 & 1.5725 & 0.00452267016866646 & 0.01 \tabularnewline
3 & 1.60083333333333 & 0.0172986249234563 & 0.05 \tabularnewline
4 & 1.58166666666667 & 0.0294906251153985 & 0.05 \tabularnewline
5 & 1.6025 & 0.0105528970602217 & 0.04 \tabularnewline
6 & 1.64416666666667 & 0.0131137217055150 & 0.0799999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2598&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]1.58916666666667[/C][C]0.0079296146109876[/C][C]0.03[/C][/ROW]
[ROW][C]2[/C][C]1.5725[/C][C]0.00452267016866646[/C][C]0.01[/C][/ROW]
[ROW][C]3[/C][C]1.60083333333333[/C][C]0.0172986249234563[/C][C]0.05[/C][/ROW]
[ROW][C]4[/C][C]1.58166666666667[/C][C]0.0294906251153985[/C][C]0.05[/C][/ROW]
[ROW][C]5[/C][C]1.6025[/C][C]0.0105528970602217[/C][C]0.04[/C][/ROW]
[ROW][C]6[/C][C]1.64416666666667[/C][C]0.0131137217055150[/C][C]0.0799999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2598&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2598&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
11.589166666666670.00792961461098760.03
21.57250.004522670168666460.01
31.600833333333330.01729862492345630.05
41.581666666666670.02949062511539850.05
51.60250.01055289706022170.04
61.644166666666670.01311372170551500.0799999999999998






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0159909898425791
beta-0.00135940069210835
S.D.0.175833198211830
T-STAT-0.00773119471142558
p-value0.99420167616906

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0159909898425791 \tabularnewline
beta & -0.00135940069210835 \tabularnewline
S.D. & 0.175833198211830 \tabularnewline
T-STAT & -0.00773119471142558 \tabularnewline
p-value & 0.99420167616906 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2598&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0159909898425791[/C][/ROW]
[ROW][C]beta[/C][C]-0.00135940069210835[/C][/ROW]
[ROW][C]S.D.[/C][C]0.175833198211830[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.00773119471142558[/C][/ROW]
[ROW][C]p-value[/C][C]0.99420167616906[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2598&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2598&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)
alpha0.0159909898425791
beta-0.00135940069210835
S.D.0.175833198211830
T-STAT-0.00773119471142558
p-value0.99420167616906






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.9208187452419
beta9.53301754731652
S.D.20.1438812742130
T-STAT0.473246313237564
p-value0.660707576483971
Lambda-8.53301754731652

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.9208187452419 \tabularnewline
beta & 9.53301754731652 \tabularnewline
S.D. & 20.1438812742130 \tabularnewline
T-STAT & 0.473246313237564 \tabularnewline
p-value & 0.660707576483971 \tabularnewline
Lambda & -8.53301754731652 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2598&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.9208187452419[/C][/ROW]
[ROW][C]beta[/C][C]9.53301754731652[/C][/ROW]
[ROW][C]S.D.[/C][C]20.1438812742130[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.473246313237564[/C][/ROW]
[ROW][C]p-value[/C][C]0.660707576483971[/C][/ROW]
[ROW][C]Lambda[/C][C]-8.53301754731652[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2598&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2598&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-8.9208187452419
beta9.53301754731652
S.D.20.1438812742130
T-STAT0.473246313237564
p-value0.660707576483971
Lambda-8.53301754731652


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')