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Description of Statistical Computation

Author's title

Spreidings-en gemiddeldegrafieken-consumptieprijsindex kleding&schoeisel-Ch...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 21 Apr 2017 13:41:33 +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/2017/Apr/21/t14927785548n7r2ug9qc1wggg.htm/, Retrieved Sun, 12 May 2024 19:31:11 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 12 May 2024 19:31:11 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.57
100.27
100.27
100.18
100.16
100.18
100.18
100.59
100.69
101.06
101.15
101.16
101.16
100.81
100.94
101.13
101.29
101.34
101.35
101.7
102.05
102.48
102.66
102.72
102.73
102.18
102.22
102.37
102.53
102.61
102.62
103
103.17
103.52
103.69
103.73
99.57
99.09
99.14
99.36
99.6
99.65
99.8
100.15
100.45
100.89
101.13
101.17
101.21
101.1
101.17
101.11
101.2
101.15
100.92
101.1
101.22
101.25
101.39
101.43
101.95
101.92
102.05
102.07
102.1
102.16
101.63
101.43
101.4
101.6
101.72
101.73
102.67
102.59
102.69
102.93
103.02
103.06
102.47
102.4
102.42
102.51
102.61
102.78

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1100.5383333333330.396778695664641
2101.6358333333330.6775552085299471.91
3102.8641666666670.5522591343881511.55
41000.7475779071593322.08
5101.18750.1348483997275880.510000000000005
6101.8133333333330.2640362693175880.759999999999991
7102.6791666666670.2265736217228430.659999999999997

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 100.538333333333 & 0.39677869566464 & 1 \tabularnewline
2 & 101.635833333333 & 0.677555208529947 & 1.91 \tabularnewline
3 & 102.864166666667 & 0.552259134388151 & 1.55 \tabularnewline
4 & 100 & 0.747577907159332 & 2.08 \tabularnewline
5 & 101.1875 & 0.134848399727588 & 0.510000000000005 \tabularnewline
6 & 101.813333333333 & 0.264036269317588 & 0.759999999999991 \tabularnewline
7 & 102.679166666667 & 0.226573621722843 & 0.659999999999997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]100.538333333333[/C][C]0.39677869566464[/C][C]1[/C][/ROW]
[ROW][C]2[/C][C]101.635833333333[/C][C]0.677555208529947[/C][C]1.91[/C][/ROW]
[ROW][C]3[/C][C]102.864166666667[/C][C]0.552259134388151[/C][C]1.55[/C][/ROW]
[ROW][C]4[/C][C]100[/C][C]0.747577907159332[/C][C]2.08[/C][/ROW]
[ROW][C]5[/C][C]101.1875[/C][C]0.134848399727588[/C][C]0.510000000000005[/C][/ROW]
[ROW][C]6[/C][C]101.813333333333[/C][C]0.264036269317588[/C][C]0.759999999999991[/C][/ROW]
[ROW][C]7[/C][C]102.679166666667[/C][C]0.226573621722843[/C][C]0.659999999999997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
1100.5383333333330.396778695664641
2101.6358333333330.6775552085299471.91
3102.8641666666670.5522591343881511.55
41000.7475779071593322.08
5101.18750.1348483997275880.510000000000005
6101.8133333333330.2640362693175880.759999999999991
7102.6791666666670.2265736217228430.659999999999997






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha7.21385606943872
beta-0.0668300802468315
S.D.0.0958284979200234
T-STAT-0.697392547075157
p-value0.516645894191097

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 7.21385606943872 \tabularnewline
beta & -0.0668300802468315 \tabularnewline
S.D. & 0.0958284979200234 \tabularnewline
T-STAT & -0.697392547075157 \tabularnewline
p-value & 0.516645894191097 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]7.21385606943872[/C][/ROW]
[ROW][C]beta[/C][C]-0.0668300802468315[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0958284979200234[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.697392547075157[/C][/ROW]
[ROW][C]p-value[/C][C]0.516645894191097[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha7.21385606943872
beta-0.0668300802468315
S.D.0.0958284979200234
T-STAT-0.697392547075157
p-value0.516645894191097






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha60.3689553552118
beta-13.2829679378508
S.D.26.6332902691311
T-STAT-0.498735522484286
p-value0.639128462309857
Lambda14.2829679378508

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 60.3689553552118 \tabularnewline
beta & -13.2829679378508 \tabularnewline
S.D. & 26.6332902691311 \tabularnewline
T-STAT & -0.498735522484286 \tabularnewline
p-value & 0.639128462309857 \tabularnewline
Lambda & 14.2829679378508 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]60.3689553552118[/C][/ROW]
[ROW][C]beta[/C][C]-13.2829679378508[/C][/ROW]
[ROW][C]S.D.[/C][C]26.6332902691311[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.498735522484286[/C][/ROW]
[ROW][C]p-value[/C][C]0.639128462309857[/C][/ROW]
[ROW][C]Lambda[/C][C]14.2829679378508[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
alpha60.3689553552118
beta-13.2829679378508
S.D.26.6332902691311
T-STAT-0.498735522484286
p-value0.639128462309857
Lambda14.2829679378508


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')