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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationSun, 22 Nov 2015 14:56:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/22/t1448204236sh000xf7vrcwb8i.htm/, Retrieved Wed, 15 May 2024 01:17:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283822, Retrieved Wed, 15 May 2024 01:17:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117

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] [datareeks- consum...] [2015-09-23 11:12:30] [4649920a4745779a23d80cc94ee68543]
- RMPD    [Standard Deviation-Mean Plot] [standaard afwijki...] [2015-11-22 14:56:43] [4bedbbf2e5251222bc39a0f973d05821] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89.56
89.84
89.97
90.65
91.17
91.35
91.41
91.55
91.63
91.54
91.74
91.87
92.13
92.14
92.05
92
92.51
92.67
92.68
92.77
92.85
92.71
92.73
92.28
92.49
92.46
92.55
92.24
92.41
92.83
92.85
93.04
93.04
92.83
92.96
92.83
93.01
93.21
93.58
94.07
94.57
95.03
95.21
95.89
96.43
96.35
96.71
96.32
97.23
97.88
98.2
98.56
99.31
99.69
99.77
101.06
101.77
101.91
102.52
102.09
102.22
102.74
103.56
104.4
104.76
104.86
104.84
104.96
104.83
104.58
104.8
104.17

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' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283822&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283822&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283822&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' @ jenkins.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
191.02333333333330.8096613583168662.31
292.460.3165151152501540.849999999999994
392.71083333333330.268072525238750.800000000000011
495.03166666666671.334485487051663.69999999999999
599.99916666666671.827295360179455.28999999999999
6104.2266666666670.9111265088622522.73999999999999

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 91.0233333333333 & 0.809661358316866 & 2.31 \tabularnewline
2 & 92.46 & 0.316515115250154 & 0.849999999999994 \tabularnewline
3 & 92.7108333333333 & 0.26807252523875 & 0.800000000000011 \tabularnewline
4 & 95.0316666666667 & 1.33448548705166 & 3.69999999999999 \tabularnewline
5 & 99.9991666666667 & 1.82729536017945 & 5.28999999999999 \tabularnewline
6 & 104.226666666667 & 0.911126508862252 & 2.73999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283822&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]91.0233333333333[/C][C]0.809661358316866[/C][C]2.31[/C][/ROW]
[ROW][C]2[/C][C]92.46[/C][C]0.316515115250154[/C][C]0.849999999999994[/C][/ROW]
[ROW][C]3[/C][C]92.7108333333333[/C][C]0.26807252523875[/C][C]0.800000000000011[/C][/ROW]
[ROW][C]4[/C][C]95.0316666666667[/C][C]1.33448548705166[/C][C]3.69999999999999[/C][/ROW]
[ROW][C]5[/C][C]99.9991666666667[/C][C]1.82729536017945[/C][C]5.28999999999999[/C][/ROW]
[ROW][C]6[/C][C]104.226666666667[/C][C]0.911126508862252[/C][C]2.73999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283822&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283822&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
191.02333333333330.8096613583168662.31
292.460.3165151152501540.849999999999994
392.71083333333330.268072525238750.800000000000011
495.03166666666671.334485487051663.69999999999999
599.99916666666671.827295360179455.28999999999999
6104.2266666666670.9111265088622522.73999999999999






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-4.85663067429625
beta0.0601387438864137
S.D.0.0497991917114287
T-STAT1.20762489951443
p-value0.293711286980951

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -4.85663067429625 \tabularnewline
beta & 0.0601387438864137 \tabularnewline
S.D. & 0.0497991917114287 \tabularnewline
T-STAT & 1.20762489951443 \tabularnewline
p-value & 0.293711286980951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283822&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-4.85663067429625[/C][/ROW]
[ROW][C]beta[/C][C]0.0601387438864137[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0497991917114287[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.20762489951443[/C][/ROW]
[ROW][C]p-value[/C][C]0.293711286980951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283822&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283822&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-4.85663067429625
beta0.0601387438864137
S.D.0.0497991917114287
T-STAT1.20762489951443
p-value0.293711286980951






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-36.3816789656233
beta7.90588728794018
S.D.6.12455206323244
T-STAT1.29085151147651
p-value0.266309510036634
Lambda-6.90588728794018

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -36.3816789656233 \tabularnewline
beta & 7.90588728794018 \tabularnewline
S.D. & 6.12455206323244 \tabularnewline
T-STAT & 1.29085151147651 \tabularnewline
p-value & 0.266309510036634 \tabularnewline
Lambda & -6.90588728794018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283822&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-36.3816789656233[/C][/ROW]
[ROW][C]beta[/C][C]7.90588728794018[/C][/ROW]
[ROW][C]S.D.[/C][C]6.12455206323244[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.29085151147651[/C][/ROW]
[ROW][C]p-value[/C][C]0.266309510036634[/C][/ROW]
[ROW][C]Lambda[/C][C]-6.90588728794018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283822&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283822&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-36.3816789656233
beta7.90588728794018
S.D.6.12455206323244
T-STAT1.29085151147651
p-value0.266309510036634
Lambda-6.90588728794018


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')