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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 computationThu, 03 Dec 2009 03:18:02 -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/Dec/03/t1259835572yp3cjv91yarmfmi.htm/, Retrieved Wed, 24 Apr 2024 16:20:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62665, Retrieved Wed, 24 Apr 2024 16:20:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
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]
- RMP   [Standard Deviation-Mean Plot] [] [2009-11-27 14:40:44] [b98453cac15ba1066b407e146608df68]
-    D    [Standard Deviation-Mean Plot] [] [2009-12-03 09:35:58] [4b0ddbda2a8eb8bbc60159112cb39d44]
-    D        [Standard Deviation-Mean Plot] [] [2009-12-03 10:18:02] [aa8eb70c35ea8a87edcd21d6427e653e] [Current]
-    D          [Standard Deviation-Mean Plot] [] [2009-12-10 11:14:55] [4b0ddbda2a8eb8bbc60159112cb39d44]
-    D          [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-28 08:29:41] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
2849,27
2921,44
2981,85
3080,58
3106,22
3119,31
3061,26
3097,31
3161,69
3257,16
3277,01
3295,32
3363,99
3494,17
3667,03
3813,06
3917,96
3895,51
3801,06
3570,12
3701,61
3862,27
3970,1
4138,52
4199,75
4290,89
4443,91
4502,64
4356,98
4591,27
4696,96
4621,4
4562,84
4202,52
4296,49
4435,23
4105,18
4116,68
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45
1862,83
1905,41
1810,99
1670,07
1864,44
2052,02
2029,6
2070,83
2293,41
2443,27
2513,17




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62665&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62665&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62665&T=0

As an alternative you can also use a 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'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13100.70166666667137.836137815447446.05
23766.28333333333217.593686252542774.53
34433.40666666667166.292423614292497.21
43488.71416666667569.678808124821918.86
52044.2075256.195138805808843.1

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3100.70166666667 & 137.836137815447 & 446.05 \tabularnewline
2 & 3766.28333333333 & 217.593686252542 & 774.53 \tabularnewline
3 & 4433.40666666667 & 166.292423614292 & 497.21 \tabularnewline
4 & 3488.71416666667 & 569.67880812482 & 1918.86 \tabularnewline
5 & 2044.2075 & 256.195138805808 & 843.1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62665&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]3100.70166666667[/C][C]137.836137815447[/C][C]446.05[/C][/ROW]
[ROW][C]2[/C][C]3766.28333333333[/C][C]217.593686252542[/C][C]774.53[/C][/ROW]
[ROW][C]3[/C][C]4433.40666666667[/C][C]166.292423614292[/C][C]497.21[/C][/ROW]
[ROW][C]4[/C][C]3488.71416666667[/C][C]569.67880812482[/C][C]1918.86[/C][/ROW]
[ROW][C]5[/C][C]2044.2075[/C][C]256.195138805808[/C][C]843.1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62665&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62665&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13100.70166666667137.836137815447446.05
23766.28333333333217.593686252542774.53
34433.40666666667166.292423614292497.21
43488.71416666667569.678808124821918.86
52044.2075256.195138805808843.1







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha314.222090679387
beta-0.0132780905551982
S.D.0.113202276865822
T-STAT-0.117295260509085
p-value0.914038181441044

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 314.222090679387 \tabularnewline
beta & -0.0132780905551982 \tabularnewline
S.D. & 0.113202276865822 \tabularnewline
T-STAT & -0.117295260509085 \tabularnewline
p-value & 0.914038181441044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62665&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]314.222090679387[/C][/ROW]
[ROW][C]beta[/C][C]-0.0132780905551982[/C][/ROW]
[ROW][C]S.D.[/C][C]0.113202276865822[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.117295260509085[/C][/ROW]
[ROW][C]p-value[/C][C]0.914038181441044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62665&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62665&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha314.222090679387
beta-0.0132780905551982
S.D.0.113202276865822
T-STAT-0.117295260509085
p-value0.914038181441044







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.15005798838812
beta-0.208573352862129
S.D.1.07823711968032
T-STAT-0.193439225060223
p-value0.858971120223681
Lambda1.20857335286213

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 7.15005798838812 \tabularnewline
beta & -0.208573352862129 \tabularnewline
S.D. & 1.07823711968032 \tabularnewline
T-STAT & -0.193439225060223 \tabularnewline
p-value & 0.858971120223681 \tabularnewline
Lambda & 1.20857335286213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62665&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.15005798838812[/C][/ROW]
[ROW][C]beta[/C][C]-0.208573352862129[/C][/ROW]
[ROW][C]S.D.[/C][C]1.07823711968032[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.193439225060223[/C][/ROW]
[ROW][C]p-value[/C][C]0.858971120223681[/C][/ROW]
[ROW][C]Lambda[/C][C]1.20857335286213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62665&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62665&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha7.15005798838812
beta-0.208573352862129
S.D.1.07823711968032
T-STAT-0.193439225060223
p-value0.858971120223681
Lambda1.20857335286213



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')