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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 computationSun, 18 Dec 2016 17:21:37 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/18/t1482078160qcwqhthnb928tdn.htm/, Retrieved Thu, 09 May 2024 02:20:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301164, Retrieved Thu, 09 May 2024 02:20:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact48

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [N1030 SD] [2016-12-18 16:21:37] [2e11ca31a00cf8de75c33c1af2d59434] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3203.4
3248.4
3446.2
3448.6
3535
3586.8
3722.4
3796.6
3755
3654.4
3485.2
3348.6
3177
3207.2
3236.2
3358.8
3436
3563.2
3588.8
3645.4
3801.2
3856.2
4056.4
3894.4
3844.4
3712.2
3765.4
3874.8
3777
3879.2
3879
4043.2
4118.8
4103.2
4188.8
4496.6
4646
4710
4713
4440
4498.2
4266.6
4253.4
4133.2

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301164&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301164&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301164&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13519.21666666667193.197279452581593.2
23568.4292.838000514712879.4
33973.55225.067006184219784.400000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3519.21666666667 & 193.197279452581 & 593.2 \tabularnewline
2 & 3568.4 & 292.838000514712 & 879.4 \tabularnewline
3 & 3973.55 & 225.067006184219 & 784.400000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301164&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]3519.21666666667[/C][C]193.197279452581[/C][C]593.2[/C][/ROW]
[ROW][C]2[/C][C]3568.4[/C][C]292.838000514712[/C][C]879.4[/C][/ROW]
[ROW][C]3[/C][C]3973.55[/C][C]225.067006184219[/C][C]784.400000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301164&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301164&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
13519.21666666667193.197279452581593.2
23568.4292.838000514712879.4
33973.55225.067006184219784.400000000001






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha316.880262354641
beta-0.0216558079388018
S.D.0.202944723046977
T-STAT-0.106707913434088
p-value0.932323724183322

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 316.880262354641 \tabularnewline
beta & -0.0216558079388018 \tabularnewline
S.D. & 0.202944723046977 \tabularnewline
T-STAT & -0.106707913434088 \tabularnewline
p-value & 0.932323724183322 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301164&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]316.880262354641[/C][/ROW]
[ROW][C]beta[/C][C]-0.0216558079388018[/C][/ROW]
[ROW][C]S.D.[/C][C]0.202944723046977[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.106707913434088[/C][/ROW]
[ROW][C]p-value[/C][C]0.932323724183322[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301164&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301164&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)
alpha316.880262354641
beta-0.0216558079388018
S.D.0.202944723046977
T-STAT-0.106707913434088
p-value0.932323724183322






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha6.69128771093882
beta-0.150777052396964
S.D.3.16205877956146
T-STAT-0.0476831908918134
p-value0.969666913258373
Lambda1.15077705239696

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 6.69128771093882 \tabularnewline
beta & -0.150777052396964 \tabularnewline
S.D. & 3.16205877956146 \tabularnewline
T-STAT & -0.0476831908918134 \tabularnewline
p-value & 0.969666913258373 \tabularnewline
Lambda & 1.15077705239696 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301164&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.69128771093882[/C][/ROW]
[ROW][C]beta[/C][C]-0.150777052396964[/C][/ROW]
[ROW][C]S.D.[/C][C]3.16205877956146[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.0476831908918134[/C][/ROW]
[ROW][C]p-value[/C][C]0.969666913258373[/C][/ROW]
[ROW][C]Lambda[/C][C]1.15077705239696[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301164&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301164&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)
alpha6.69128771093882
beta-0.150777052396964
S.D.3.16205877956146
T-STAT-0.0476831908918134
p-value0.969666913258373
Lambda1.15077705239696


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')