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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 08:24:23 -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/t1228749999rdlpxfzk7jr4xos.htm/, Retrieved Thu, 16 May 2024 15:35:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30538, Retrieved Thu, 16 May 2024 15:35:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

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 RMPD    [Standard Deviation-Mean Plot] [standard mean plot] [2008-12-08 15:24:23] [96839c4b6d4e03ef3851369c676780bf] [Current]
Feedback Forum
2008-12-15 13:30:22 [Bert Moons] [reply] 
Ook hier werd onvoldoende uitleg geven over het al dan niet significant zijn van de lambda.
Beta is meer dan 2 maal de standaardafwijking verschillend van 0. De P-waarde is echter hoger dan 5%.
We kunnen dus twijfelen over de geldigheid van lambda.

Verder werd er afgesproken om lambda = 1 te nemen als deze buiten het interval [-2;2] viel. Wat hier het geval is.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684
1,457
1,4718
1,4748
1,5527
1,575
1,5557
1,5553
1,577
1,4975
1,4369
1,3322
1,2732

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30538&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]0 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=30538&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30538&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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
11.223241666666670.02684624430592360.0944
21.267750.04972951382684680.1393
31.2352250.03941264506359720.102500000000000
41.34430.0390734273806730.1346
51.496191666666670.07182071691920010.2448

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1.22324166666667 & 0.0268462443059236 & 0.0944 \tabularnewline
2 & 1.26775 & 0.0497295138268468 & 0.1393 \tabularnewline
3 & 1.235225 & 0.0394126450635972 & 0.102500000000000 \tabularnewline
4 & 1.3443 & 0.039073427380673 & 0.1346 \tabularnewline
5 & 1.49619166666667 & 0.0718207169192001 & 0.2448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30538&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]1.22324166666667[/C][C]0.0268462443059236[/C][C]0.0944[/C][/ROW]
[ROW][C]2[/C][C]1.26775[/C][C]0.0497295138268468[/C][C]0.1393[/C][/ROW]
[ROW][C]3[/C][C]1.235225[/C][C]0.0394126450635972[/C][C]0.102500000000000[/C][/ROW]
[ROW][C]4[/C][C]1.3443[/C][C]0.039073427380673[/C][C]0.1346[/C][/ROW]
[ROW][C]5[/C][C]1.49619166666667[/C][C]0.0718207169192001[/C][C]0.2448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30538&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30538&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
11.223241666666670.02684624430592360.0944
21.267750.04972951382684680.1393
31.2352250.03941264506359720.102500000000000
41.34430.0390734273806730.1346
51.496191666666670.07182071691920010.2448






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-0.125029033799799
beta0.129749590395275
S.D.0.0431785584062445
T-STAT3.00495419913117
p-value0.0574418322710474

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.125029033799799 \tabularnewline
beta & 0.129749590395275 \tabularnewline
S.D. & 0.0431785584062445 \tabularnewline
T-STAT & 3.00495419913117 \tabularnewline
p-value & 0.0574418322710474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30538&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.125029033799799[/C][/ROW]
[ROW][C]beta[/C][C]0.129749590395275[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0431785584062445[/C][/ROW]
[ROW][C]T-STAT[/C][C]3.00495419913117[/C][/ROW]
[ROW][C]p-value[/C][C]0.0574418322710474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30538&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30538&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-0.125029033799799
beta0.129749590395275
S.D.0.0431785584062445
T-STAT3.00495419913117
p-value0.0574418322710474






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-4.10836746987409
beta3.56872485416565
S.D.1.44263083921052
T-STAT2.47376165625202
p-value0.0897645583681788
Lambda-2.56872485416565

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -4.10836746987409 \tabularnewline
beta & 3.56872485416565 \tabularnewline
S.D. & 1.44263083921052 \tabularnewline
T-STAT & 2.47376165625202 \tabularnewline
p-value & 0.0897645583681788 \tabularnewline
Lambda & -2.56872485416565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30538&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.10836746987409[/C][/ROW]
[ROW][C]beta[/C][C]3.56872485416565[/C][/ROW]
[ROW][C]S.D.[/C][C]1.44263083921052[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.47376165625202[/C][/ROW]
[ROW][C]p-value[/C][C]0.0897645583681788[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.56872485416565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30538&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30538&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-4.10836746987409
beta3.56872485416565
S.D.1.44263083921052
T-STAT2.47376165625202
p-value0.0897645583681788
Lambda-2.56872485416565


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')