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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, 06 Dec 2008 07:17:16 -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/2008/Dec/06/t1228573097tkrmwzjc29lxjmg.htm/, Retrieved Sun, 19 May 2024 10:23:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29629, Retrieved Sun, 19 May 2024 10:23:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact233

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Standard Deviation-Mean Plot] [Identification an...] [2008-12-04 19:58:38] [063e4b67ad7d3a8a83eccec794cd5aa7]
F    D      [Standard Deviation-Mean Plot] [Eigen tijdreeks SMP] [2008-12-06 14:17:16] [6797a1f4a60918966297e9d9220cabc2] [Current]
F    D        [Standard Deviation-Mean Plot] [Eigen tijdreeks t...] [2008-12-06 14:29:21] [063e4b67ad7d3a8a83eccec794cd5aa7]
-    D        [Standard Deviation-Mean Plot] [Eigen tijdreeks t...] [2008-12-06 14:32:39] [063e4b67ad7d3a8a83eccec794cd5aa7]
-    D        [Standard Deviation-Mean Plot] [Eigen tijdreeks t...] [2008-12-06 14:36:43] [063e4b67ad7d3a8a83eccec794cd5aa7]
-    D        [Standard Deviation-Mean Plot] [] [2008-12-09 19:53:20] [888addc516c3b812dd7be4bd54caa358]
- RM D        [Variance Reduction Matrix] [] [2008-12-09 19:58:06] [888addc516c3b812dd7be4bd54caa358]
- RMPD        [(Partial) Autocorrelation Function] [] [2008-12-09 20:05:54] [888addc516c3b812dd7be4bd54caa358]
- RMPD        [(Partial) Autocorrelation Function] [AutoCorrelation F...] [2008-12-09 20:05:54] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-12-15 18:39:03 [Jeroen Michel] [reply] 
Ook hier stelt de student duidelijk hoe de data, grafieken, en tabellen moeten worden afgelezen. Op die manier kan de lezer van dit werk meteen de resultaten interpreteren. Ook hier hangt dus een zeer uitgebreide analyse aan vast.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,4
7,2
7,1
6,9
6,8
6,8
6,8
6,9
6,7
6,6
6,5
6,4
6,3
6,3
6,3
6,5
6,6
6,5
6,4
6,5
6,7
7,1
7,1
7,2
7,2
7,3
7,3
7,3
7,3
7,4
7,6
7,6
7,6
7,7
7,8
7,9
8,1
8,1
8,1
8,2
8,2
8,2
8,2
8,2
8,2
8,3
8,3
8,4
8,4
8,4
8,3
8
8
8,2
8,6
8,7
8,7
8,5
8,4
8,4
8,4
8,5
8,5
8,5
8,5
8,5
8,4
8,4
8,4
8,5
8,6
8,6
8,6
8,6
8,5
8,4
8,4
8,3
8,2
8,1
8,2
8,1
8
7,9
7,8
7,7
7,7
7,9
7,8
7,6
7,4
7,3
7,1
7,1
7
7
7
6,9
6,8
6,7
6,6
6,6

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29629&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29629&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29629&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'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
16.841666666666670.2874917653629671
26.6250.3306330017076060.9
37.50.2296241989148200.7
48.208333333333330.09003366373785240.300000000000001
58.383333333333330.2329000305762630.700
68.483333333333330.07177405625652710.199999999999999
78.2750.2301185465244930.700
87.450.3397860289278320.9

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6.84166666666667 & 0.287491765362967 & 1 \tabularnewline
2 & 6.625 & 0.330633001707606 & 0.9 \tabularnewline
3 & 7.5 & 0.229624198914820 & 0.7 \tabularnewline
4 & 8.20833333333333 & 0.0900336637378524 & 0.300000000000001 \tabularnewline
5 & 8.38333333333333 & 0.232900030576263 & 0.700 \tabularnewline
6 & 8.48333333333333 & 0.0717740562565271 & 0.199999999999999 \tabularnewline
7 & 8.275 & 0.230118546524493 & 0.700 \tabularnewline
8 & 7.45 & 0.339786028927832 & 0.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29629&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]6.84166666666667[/C][C]0.287491765362967[/C][C]1[/C][/ROW]
[ROW][C]2[/C][C]6.625[/C][C]0.330633001707606[/C][C]0.9[/C][/ROW]
[ROW][C]3[/C][C]7.5[/C][C]0.229624198914820[/C][C]0.7[/C][/ROW]
[ROW][C]4[/C][C]8.20833333333333[/C][C]0.0900336637378524[/C][C]0.300000000000001[/C][/ROW]
[ROW][C]5[/C][C]8.38333333333333[/C][C]0.232900030576263[/C][C]0.700[/C][/ROW]
[ROW][C]6[/C][C]8.48333333333333[/C][C]0.0717740562565271[/C][C]0.199999999999999[/C][/ROW]
[ROW][C]7[/C][C]8.275[/C][C]0.230118546524493[/C][C]0.700[/C][/ROW]
[ROW][C]8[/C][C]7.45[/C][C]0.339786028927832[/C][C]0.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29629&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29629&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
16.841666666666670.2874917653629671
26.6250.3306330017076060.9
37.50.2296241989148200.7
48.208333333333330.09003366373785240.300000000000001
58.383333333333330.2329000305762630.700
68.483333333333330.07177405625652710.199999999999999
78.2750.2301185465244930.700
87.450.3397860289278320.9






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha1.02239486419254
beta-0.103078212976772
S.D.0.0376433817568042
T-STAT-2.73828248595491
p-value0.0338125887818792

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1.02239486419254 \tabularnewline
beta & -0.103078212976772 \tabularnewline
S.D. & 0.0376433817568042 \tabularnewline
T-STAT & -2.73828248595491 \tabularnewline
p-value & 0.0338125887818792 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29629&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1.02239486419254[/C][/ROW]
[ROW][C]beta[/C][C]-0.103078212976772[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0376433817568042[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.73828248595491[/C][/ROW]
[ROW][C]p-value[/C][C]0.0338125887818792[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29629&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29629&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)
alpha1.02239486419254
beta-0.103078212976772
S.D.0.0376433817568042
T-STAT-2.73828248595491
p-value0.0338125887818792






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.86543426851966
beta-4.15421178322162
S.D.1.84065983758473
T-STAT-2.2569144490449
p-value0.0648223459979466
Lambda5.15421178322162

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.86543426851966 \tabularnewline
beta & -4.15421178322162 \tabularnewline
S.D. & 1.84065983758473 \tabularnewline
T-STAT & -2.2569144490449 \tabularnewline
p-value & 0.0648223459979466 \tabularnewline
Lambda & 5.15421178322162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29629&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.86543426851966[/C][/ROW]
[ROW][C]beta[/C][C]-4.15421178322162[/C][/ROW]
[ROW][C]S.D.[/C][C]1.84065983758473[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.2569144490449[/C][/ROW]
[ROW][C]p-value[/C][C]0.0648223459979466[/C][/ROW]
[ROW][C]Lambda[/C][C]5.15421178322162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29629&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29629&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)
alpha6.86543426851966
beta-4.15421178322162
S.D.1.84065983758473
T-STAT-2.2569144490449
p-value0.0648223459979466
Lambda5.15421178322162


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')