FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 25 Nov 2009 09:13:35 -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/25/t12591656605csxbiykmhar31p.htm/, Retrieved Wed, 08 May 2024 19:03:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59428, Retrieved Wed, 08 May 2024 19:03:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop 8
Estimated Impact147

Tree of Dependent Computations

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] [workshop 8] [2009-11-25 16:13:35] [6198946fb53eb5eb18db46bb758f7fde] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.6348
0.634
0.62915
0.62168
0.61328
0.6089
0.60857
0.62672
0.62291
0.62393
0.61838
0.62012
0.61659
0.6116
0.61573
0.61407
0.62823
0.64405
0.6387
0.63633
0.63059
0.62994
0.63709
0.64217
0.65711
0.66977
0.68255
0.68902
0.71322
0.70224
0.70045
0.69919
0.69693
0.69763
0.69278
0.70196
0.69215
0.6769
0.67124
0.66532
0.67157
0.66428
0.66576
0.66942
0.6813
0.69144
0.69862
0.695
0.69867
0.68968
0.69233
0.68293
0.68399
0.66895
0.68756
0.68527
0.6776
0.68137
0.67933
0.67922

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'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=59428&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=59428&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59428&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.621870.008688265858982650.0262300000000000
20.62875750.01156909372187180.03245
30.6919041666666670.01550253378605830.05611
40.6785833333333330.01265828678148920.0343400000000000
50.6839083333333330.007694316477803980.02972

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.62187 & 0.00868826585898265 & 0.0262300000000000 \tabularnewline
2 & 0.6287575 & 0.0115690937218718 & 0.03245 \tabularnewline
3 & 0.691904166666667 & 0.0155025337860583 & 0.05611 \tabularnewline
4 & 0.678583333333333 & 0.0126582867814892 & 0.0343400000000000 \tabularnewline
5 & 0.683908333333333 & 0.00769431647780398 & 0.02972 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59428&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]0.62187[/C][C]0.00868826585898265[/C][C]0.0262300000000000[/C][/ROW]
[ROW][C]2[/C][C]0.6287575[/C][C]0.0115690937218718[/C][C]0.03245[/C][/ROW]
[ROW][C]3[/C][C]0.691904166666667[/C][C]0.0155025337860583[/C][C]0.05611[/C][/ROW]
[ROW][C]4[/C][C]0.678583333333333[/C][C]0.0126582867814892[/C][C]0.0343400000000000[/C][/ROW]
[ROW][C]5[/C][C]0.683908333333333[/C][C]0.00769431647780398[/C][C]0.02972[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59428&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59428&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
10.621870.008688265858982650.0262300000000000
20.62875750.01156909372187180.03245
30.6919041666666670.01550253378605830.05611
40.6785833333333330.01265828678148920.0343400000000000
50.6839083333333330.007694316477803980.02972






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.0137456285256222
beta0.0377729978470097
S.D.0.0503443550262569
T-STAT0.750292616268684
p-value0.507562059278588

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.0137456285256222 \tabularnewline
beta & 0.0377729978470097 \tabularnewline
S.D. & 0.0503443550262569 \tabularnewline
T-STAT & 0.750292616268684 \tabularnewline
p-value & 0.507562059278588 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59428&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.0137456285256222[/C][/ROW]
[ROW][C]beta[/C][C]0.0377729978470097[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0503443550262569[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.750292616268684[/C][/ROW]
[ROW][C]p-value[/C][C]0.507562059278588[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59428&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59428&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)
alpha-0.0137456285256222
beta0.0377729978470097
S.D.0.0503443550262569
T-STAT0.750292616268684
p-value0.507562059278588






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.7453795057557
beta1.87071394997626
S.D.3.06965911592674
T-STAT0.609420746515523
p-value0.585299058446252
Lambda-0.870713949976256

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.7453795057557 \tabularnewline
beta & 1.87071394997626 \tabularnewline
S.D. & 3.06965911592674 \tabularnewline
T-STAT & 0.609420746515523 \tabularnewline
p-value & 0.585299058446252 \tabularnewline
Lambda & -0.870713949976256 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59428&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.7453795057557[/C][/ROW]
[ROW][C]beta[/C][C]1.87071394997626[/C][/ROW]
[ROW][C]S.D.[/C][C]3.06965911592674[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.609420746515523[/C][/ROW]
[ROW][C]p-value[/C][C]0.585299058446252[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.870713949976256[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59428&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59428&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-3.7453795057557
beta1.87071394997626
S.D.3.06965911592674
T-STAT0.609420746515523
p-value0.585299058446252
Lambda-0.870713949976256


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')