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Description of Statistical Computation

Author's title

Wisselkoersen - Referentiewisselkoersen voor de euro in nationale munteenhe...

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 30 May 2008 13:45:30 -0600
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/May/30/t1212176781l5269rl1f30d01q.htm/, Retrieved Tue, 14 May 2024 08:55:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13557, Retrieved Tue, 14 May 2024 08:55:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact253

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] [Wisselkoersen - R...] [2008-05-30 19:45:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,9383
0,9217
0,9095
0,892
0,8742
0,8532
0,8607
0,9005
0,9111
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
1,1692
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13557&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]4 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=13557&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13557&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
10.895650.02452874010032090.0851
20.9449083333333330.05482170204537170.1483
31.13090.04972414814846910.1664
41.243333333333330.04244370246323800.1423
51.2447750.05156309682850180.1415
61.255658333333330.03886141948311230.1275
71.370633333333330.05467872003112750.1685

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.89565 & 0.0245287401003209 & 0.0851 \tabularnewline
2 & 0.944908333333333 & 0.0548217020453717 & 0.1483 \tabularnewline
3 & 1.1309 & 0.0497241481484691 & 0.1664 \tabularnewline
4 & 1.24333333333333 & 0.0424437024632380 & 0.1423 \tabularnewline
5 & 1.244775 & 0.0515630968285018 & 0.1415 \tabularnewline
6 & 1.25565833333333 & 0.0388614194831123 & 0.1275 \tabularnewline
7 & 1.37063333333333 & 0.0546787200311275 & 0.1685 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13557&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]0.89565[/C][C]0.0245287401003209[/C][C]0.0851[/C][/ROW]
[ROW][C]2[/C][C]0.944908333333333[/C][C]0.0548217020453717[/C][C]0.1483[/C][/ROW]
[ROW][C]3[/C][C]1.1309[/C][C]0.0497241481484691[/C][C]0.1664[/C][/ROW]
[ROW][C]4[/C][C]1.24333333333333[/C][C]0.0424437024632380[/C][C]0.1423[/C][/ROW]
[ROW][C]5[/C][C]1.244775[/C][C]0.0515630968285018[/C][C]0.1415[/C][/ROW]
[ROW][C]6[/C][C]1.25565833333333[/C][C]0.0388614194831123[/C][C]0.1275[/C][/ROW]
[ROW][C]7[/C][C]1.37063333333333[/C][C]0.0546787200311275[/C][C]0.1685[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13557&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13557&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
10.895650.02452874010032090.0851
20.9449083333333330.05482170204537170.1483
31.13090.04972414814846910.1664
41.243333333333330.04244370246323800.1423
51.2447750.05156309682850180.1415
61.255658333333330.03886141948311230.1275
71.370633333333330.05467872003112750.1685






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha0.0141468346156055
beta0.0269104005809612
S.D.0.0251810075355886
T-STAT1.06867846899805
p-value0.334070490368463

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0141468346156055 \tabularnewline
beta & 0.0269104005809612 \tabularnewline
S.D. & 0.0251810075355886 \tabularnewline
T-STAT & 1.06867846899805 \tabularnewline
p-value & 0.334070490368463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13557&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0141468346156055[/C][/ROW]
[ROW][C]beta[/C][C]0.0269104005809612[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0251810075355886[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.06867846899805[/C][/ROW]
[ROW][C]p-value[/C][C]0.334070490368463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13557&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13557&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)
alpha0.0141468346156055
beta0.0269104005809612
S.D.0.0251810075355886
T-STAT1.06867846899805
p-value0.334070490368463






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-3.24841295999845
beta0.905605109272991
S.D.0.696951172436896
T-STAT1.29938099695928
p-value0.250496900142516
Lambda0.094394890727009

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -3.24841295999845 \tabularnewline
beta & 0.905605109272991 \tabularnewline
S.D. & 0.696951172436896 \tabularnewline
T-STAT & 1.29938099695928 \tabularnewline
p-value & 0.250496900142516 \tabularnewline
Lambda & 0.094394890727009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13557&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-3.24841295999845[/C][/ROW]
[ROW][C]beta[/C][C]0.905605109272991[/C][/ROW]
[ROW][C]S.D.[/C][C]0.696951172436896[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.29938099695928[/C][/ROW]
[ROW][C]p-value[/C][C]0.250496900142516[/C][/ROW]
[ROW][C]Lambda[/C][C]0.094394890727009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13557&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13557&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-3.24841295999845
beta0.905605109272991
S.D.0.696951172436896
T-STAT1.29938099695928
p-value0.250496900142516
Lambda0.094394890727009


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')