Free Statistics

of Irreproducible Research!

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 computationFri, 27 Nov 2009 07:04:08 -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/27/t12593307646y29zfbm3f31x66.htm/, Retrieved Mon, 29 Apr 2024 01:48:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60790, Retrieved Mon, 29 Apr 2024 01:48:38 +0000
QR Codes:

Original text written by user:SMP (3)
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135
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]
-    D          [Standard Deviation-Mean Plot] [Shw8: Method: SMP...] [2009-11-27 14:04:08] [7a39e26d7a09dd77604df90cb29f8d39] [Current]
-                 [Standard Deviation-Mean Plot] [Workshop 8: Metho...] [2009-12-03 16:07:23] [986783eb96d1bee9537f9dc51fad07f7]
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Dataseries X:
5.22751
4.14188
4.09705
4.23638
3.77166
4.31445
4.03524
4.86342
4.58265
4.72760
5.18813
4.65792
5.12583
5.52174
5.74640
5.03781
5.55138
6.60125
4.91829
4.58604
5.33969
4.51214
4.61668
5.15297
4.40067
3.92333
3.75018
4.31129
3.83973
3.35638
2.92703
2.97547
2.52531
2.38712
3.03736
2.02295
1.58571
1.97447
2.03724
1.95074
1.36328
1.62114
1.47311
1.29005
1.24016
1.38960
2.28445
3.53559
9.76023
10.70122
7.94442
12.02136
11.85404
8.31016
6.07548
3.75285
3.25489
2.90117
2.68923




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=60790&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=60790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60790&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
14.486990833333330.4629384799391101.45585
25.225851666666670.5880841204644322.08911
33.288068333333330.7684648415667712.37772
41.812128333333330.6376116630453962.29543

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4.48699083333333 & 0.462938479939110 & 1.45585 \tabularnewline
2 & 5.22585166666667 & 0.588084120464432 & 2.08911 \tabularnewline
3 & 3.28806833333333 & 0.768464841566771 & 2.37772 \tabularnewline
4 & 1.81212833333333 & 0.637611663045396 & 2.29543 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60790&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]4.48699083333333[/C][C]0.462938479939110[/C][C]1.45585[/C][/ROW]
[ROW][C]2[/C][C]5.22585166666667[/C][C]0.588084120464432[/C][C]2.08911[/C][/ROW]
[ROW][C]3[/C][C]3.28806833333333[/C][C]0.768464841566771[/C][C]2.37772[/C][/ROW]
[ROW][C]4[/C][C]1.81212833333333[/C][C]0.637611663045396[/C][C]2.29543[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60790&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
14.486990833333330.4629384799391101.45585
25.225851666666670.5880841204644322.08911
33.288068333333330.7684648415667712.37772
41.812128333333330.6376116630453962.29543







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.762064207260215
beta-0.0399079295864831
S.D.0.0528100774856983
T-STAT-0.755687768064547
p-value0.528712470110998

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.762064207260215 \tabularnewline
beta & -0.0399079295864831 \tabularnewline
S.D. & 0.0528100774856983 \tabularnewline
T-STAT & -0.755687768064547 \tabularnewline
p-value & 0.528712470110998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60790&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.762064207260215[/C][/ROW]
[ROW][C]beta[/C][C]-0.0399079295864831[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0528100774856983[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.755687768064547[/C][/ROW]
[ROW][C]p-value[/C][C]0.528712470110998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60790&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60790&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)
alpha0.762064207260215
beta-0.0399079295864831
S.D.0.0528100774856983
T-STAT-0.755687768064547
p-value0.528712470110998







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-0.264576207578670
beta-0.193563735007198
S.D.0.286028555155462
T-STAT-0.676728709488436
p-value0.56835467502454
Lambda1.19356373500720

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.264576207578670 \tabularnewline
beta & -0.193563735007198 \tabularnewline
S.D. & 0.286028555155462 \tabularnewline
T-STAT & -0.676728709488436 \tabularnewline
p-value & 0.56835467502454 \tabularnewline
Lambda & 1.19356373500720 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60790&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.264576207578670[/C][/ROW]
[ROW][C]beta[/C][C]-0.193563735007198[/C][/ROW]
[ROW][C]S.D.[/C][C]0.286028555155462[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.676728709488436[/C][/ROW]
[ROW][C]p-value[/C][C]0.56835467502454[/C][/ROW]
[ROW][C]Lambda[/C][C]1.19356373500720[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60790&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60790&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)
alpha-0.264576207578670
beta-0.193563735007198
S.D.0.286028555155462
T-STAT-0.676728709488436
p-value0.56835467502454
Lambda1.19356373500720



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')