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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 computationMon, 08 Dec 2008 06:40:16 -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/08/t1228743928lx8nqzf5swyoydd.htm/, Retrieved Thu, 16 May 2024 23:14:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30488, Retrieved Thu, 16 May 2024 23:14:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact162

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [VRM PAPER] [2008-12-08 12:10:16] [547636b63517c1c2916a747d66b36ebf]
- RMPD  [Spectral Analysis] [SPECTRUM zonder a...] [2008-12-08 12:48:15] [547636b63517c1c2916a747d66b36ebf]
-   P     [Spectral Analysis] [SPECTRUM met aang...] [2008-12-08 12:53:34] [547636b63517c1c2916a747d66b36ebf]
- RMP         [Standard Deviation-Mean Plot] [SDMP PAPER LAMBDA...] [2008-12-08 13:40:16] [e11d930c9e2984715c66c796cf63ef19] [Current]
- RM            [(Partial) Autocorrelation Function] [PACF zonder aagep...] [2008-12-08 13:59:46] [547636b63517c1c2916a747d66b36ebf]
-                 [(Partial) Autocorrelation Function] [PACF met aangepas...] [2008-12-08 14:08:36] [547636b63517c1c2916a747d66b36ebf]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12300.00
12092.80
12380.80
12196.90
9455.00
13168.00
13427.90
11980.50
11884.80
11691.70
12233.80
14341.40
13130.70
12421.10
14285.80
12864.60
11160.20
14316.20
14388.70
14013.90
13419.00
12769.60
13315.50
15332.90
14243.00
13824.40
14962.90
13202.90
12199.00
15508.90
14199.80
15169.60
14058.00
13786.20
14147.90
16541.70
13587.50
15582.40
15802.80
14130.50
12923.20
15612.20
16033.70
16036.60
14037.80
15330.60
15038.30
17401.80
14992.50
16043.70
16929.60
15921.30
14417.20
15961.00
17851.90
16483.90
14215.50
17429.70
17839.50
17629.20

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30488&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]2 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=30488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30488&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
112262.81166.94192423854886.4
213451.51666666671104.608120419624172.7
314320.35833333331123.320070520124342.7
415126.451249.697655435114478.6
516309.58333333331285.379979074693636.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 12262.8 & 1166.9419242385 & 4886.4 \tabularnewline
2 & 13451.5166666667 & 1104.60812041962 & 4172.7 \tabularnewline
3 & 14320.3583333333 & 1123.32007052012 & 4342.7 \tabularnewline
4 & 15126.45 & 1249.69765543511 & 4478.6 \tabularnewline
5 & 16309.5833333333 & 1285.37997907469 & 3636.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30488&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]12262.8[/C][C]1166.9419242385[/C][C]4886.4[/C][/ROW]
[ROW][C]2[/C][C]13451.5166666667[/C][C]1104.60812041962[/C][C]4172.7[/C][/ROW]
[ROW][C]3[/C][C]14320.3583333333[/C][C]1123.32007052012[/C][C]4342.7[/C][/ROW]
[ROW][C]4[/C][C]15126.45[/C][C]1249.69765543511[/C][C]4478.6[/C][/ROW]
[ROW][C]5[/C][C]16309.5833333333[/C][C]1285.37997907469[/C][C]3636.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30488&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
112262.81166.94192423854886.4
213451.51666666671104.608120419624172.7
314320.35833333331123.320070520124342.7
415126.451249.697655435114478.6
516309.58333333331285.379979074693636.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha651.045108658678
beta0.037424033828236
S.D.0.0199184879357295
T-STAT1.87885917590688
p-value0.15687196614732

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 651.045108658678 \tabularnewline
beta & 0.037424033828236 \tabularnewline
S.D. & 0.0199184879357295 \tabularnewline
T-STAT & 1.87885917590688 \tabularnewline
p-value & 0.15687196614732 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30488&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]651.045108658678[/C][/ROW]
[ROW][C]beta[/C][C]0.037424033828236[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0199184879357295[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.87885917590688[/C][/ROW]
[ROW][C]p-value[/C][C]0.15687196614732[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30488&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30488&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)
alpha651.045108658678
beta0.037424033828236
S.D.0.0199184879357295
T-STAT1.87885917590688
p-value0.15687196614732






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.01780676398127
beta0.424430695982864
S.D.0.249063513249117
T-STAT1.70410627572872
p-value0.186909408728279
Lambda0.575569304017136

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.01780676398127 \tabularnewline
beta & 0.424430695982864 \tabularnewline
S.D. & 0.249063513249117 \tabularnewline
T-STAT & 1.70410627572872 \tabularnewline
p-value & 0.186909408728279 \tabularnewline
Lambda & 0.575569304017136 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30488&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.01780676398127[/C][/ROW]
[ROW][C]beta[/C][C]0.424430695982864[/C][/ROW]
[ROW][C]S.D.[/C][C]0.249063513249117[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.70410627572872[/C][/ROW]
[ROW][C]p-value[/C][C]0.186909408728279[/C][/ROW]
[ROW][C]Lambda[/C][C]0.575569304017136[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30488&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30488&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)
alpha3.01780676398127
beta0.424430695982864
S.D.0.249063513249117
T-STAT1.70410627572872
p-value0.186909408728279
Lambda0.575569304017136


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')