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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, 09 Aug 2015 18:04:17 +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/2015/Aug/09/t1439139957d35g5bw7b88fahe.htm/, Retrieved Wed, 15 May 2024 21:38:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279958, Retrieved Wed, 15 May 2024 21:38:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsStandard Deviation Mean Plot Sebastiaan Lunders Reeks A Omzet Mercedes A-klasse euro Ottevaere MAR204A sebastiaan.lunders@student.kdg.be
Estimated Impact132

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] [Cijferreeks A 2de...] [2015-08-05 23:58:24] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP   [(Partial) Autocorrelation Function] [Autocorrelation R...] [2015-08-09 16:24:48] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP     [Standard Deviation Plot] [Standard Deviatio...] [2015-08-09 16:43:04] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RM          [Standard Deviation-Mean Plot] [Standard Deviatio...] [2015-08-09 17:04:17] [2cf7618d5ff65529ef2e27cea5366de0] [Current]
- RMP           [Classical Decomposition] [Classic Decomposi...] [2015-08-09 17:24:10] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP             [Exponential Smoothing] [Exponential Smoot...] [2015-08-09 17:45:12] [039d3b62ab99f9eeb4c9cc4c099c66fc]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3221816.00
3209817.00
3197649.00
3172468.00
3421574.00
3408392.00
3221816.00
3097770.00
3109769.00
3109769.00
3123120.00
3147118.00
3184467.00
3184467.00
3160469.00
3097770.00
3421574.00
3470922.00
3396393.00
3221816.00
3296514.00
3184467.00
3234998.00
3259165.00
3284346.00
3221816.00
3234998.00
3147118.00
3421574.00
3508271.00
3433742.00
3296514.00
3445741.00
3284346.00
3433742.00
3421574.00
3458923.00
3321695.00
3470922.00
3458923.00
3682848.00
3632317.00
3433742.00
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3470922.00
3284346.00
3421574.00
3445741.00
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3445741.00
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3620318.00
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3359044.00
3197649.00
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3135119.00
3246997.00
3359044.00
3197649.00
3197649.00
3197649.00
3284346.00
3160469.00
2997891.00
2861846.00
2960542.00
2575222.00
2811315.00
2948543.00
2973724.00
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2848495.00
2811315.00
2936375.00
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2550041.00
2761798.00
2301949.00
2600572.00
2736617.00
2736617.00
2575222.00
2425995.00
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2550041.00
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2190071.00
2027493.00
2202070.00
1791569.00
2164721.00
2363296.00
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1828749.00
1878097.00
1779401.00
1406249.00
1243671.00
1392898.00
982397.00
1430247.00
1704872.00

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279958&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279958&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279958&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'Herman Ole Andreas Wold' @ wold.wessa.net






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
13203423.16666667108558.619971661323804
23259418.5115187.997603522373152
33344481.83333333112984.760860467361153
43451303.91666667115598.436106485398502
53346692.91666667190362.925468198683943
63046013.75226963.723906837783822
72740095.58333333186649.748390576671775
82322257.16666667260147.799653768945048
92024676.33333333290489.914081315970398
101614076.75321492.2215106311107626

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 3203423.16666667 & 108558.619971661 & 323804 \tabularnewline
2 & 3259418.5 & 115187.997603522 & 373152 \tabularnewline
3 & 3344481.83333333 & 112984.760860467 & 361153 \tabularnewline
4 & 3451303.91666667 & 115598.436106485 & 398502 \tabularnewline
5 & 3346692.91666667 & 190362.925468198 & 683943 \tabularnewline
6 & 3046013.75 & 226963.723906837 & 783822 \tabularnewline
7 & 2740095.58333333 & 186649.748390576 & 671775 \tabularnewline
8 & 2322257.16666667 & 260147.799653768 & 945048 \tabularnewline
9 & 2024676.33333333 & 290489.914081315 & 970398 \tabularnewline
10 & 1614076.75 & 321492.221510631 & 1107626 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279958&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]3203423.16666667[/C][C]108558.619971661[/C][C]323804[/C][/ROW]
[ROW][C]2[/C][C]3259418.5[/C][C]115187.997603522[/C][C]373152[/C][/ROW]
[ROW][C]3[/C][C]3344481.83333333[/C][C]112984.760860467[/C][C]361153[/C][/ROW]
[ROW][C]4[/C][C]3451303.91666667[/C][C]115598.436106485[/C][C]398502[/C][/ROW]
[ROW][C]5[/C][C]3346692.91666667[/C][C]190362.925468198[/C][C]683943[/C][/ROW]
[ROW][C]6[/C][C]3046013.75[/C][C]226963.723906837[/C][C]783822[/C][/ROW]
[ROW][C]7[/C][C]2740095.58333333[/C][C]186649.748390576[/C][C]671775[/C][/ROW]
[ROW][C]8[/C][C]2322257.16666667[/C][C]260147.799653768[/C][C]945048[/C][/ROW]
[ROW][C]9[/C][C]2024676.33333333[/C][C]290489.914081315[/C][C]970398[/C][/ROW]
[ROW][C]10[/C][C]1614076.75[/C][C]321492.221510631[/C][C]1107626[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279958&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279958&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
13203423.16666667108558.619971661323804
23259418.5115187.997603522373152
33344481.83333333112984.760860467361153
43451303.91666667115598.436106485398502
53346692.91666667190362.925468198683943
63046013.75226963.723906837783822
72740095.58333333186649.748390576671775
82322257.16666667260147.799653768945048
92024676.33333333290489.914081315970398
101614076.75321492.2215106311107626






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha513656.553791114
beta-0.113151792219188
S.D.0.0185894327362385
T-STAT-6.08688784777213
p-value0.000293686871073616

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 513656.553791114 \tabularnewline
beta & -0.113151792219188 \tabularnewline
S.D. & 0.0185894327362385 \tabularnewline
T-STAT & -6.08688784777213 \tabularnewline
p-value & 0.000293686871073616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279958&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]513656.553791114[/C][/ROW]
[ROW][C]beta[/C][C]-0.113151792219188[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0185894327362385[/C][/ROW]
[ROW][C]T-STAT[/C][C]-6.08688784777213[/C][/ROW]
[ROW][C]p-value[/C][C]0.000293686871073616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279958&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279958&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)
alpha513656.553791114
beta-0.113151792219188
S.D.0.0185894327362385
T-STAT-6.08688784777213
p-value0.000293686871073616






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha32.6429898907453
beta-1.38589065989076
S.D.0.316605261909547
T-STAT-4.37734563074542
p-value0.00235715681397511
Lambda2.38589065989076

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 32.6429898907453 \tabularnewline
beta & -1.38589065989076 \tabularnewline
S.D. & 0.316605261909547 \tabularnewline
T-STAT & -4.37734563074542 \tabularnewline
p-value & 0.00235715681397511 \tabularnewline
Lambda & 2.38589065989076 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279958&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]32.6429898907453[/C][/ROW]
[ROW][C]beta[/C][C]-1.38589065989076[/C][/ROW]
[ROW][C]S.D.[/C][C]0.316605261909547[/C][/ROW]
[ROW][C]T-STAT[/C][C]-4.37734563074542[/C][/ROW]
[ROW][C]p-value[/C][C]0.00235715681397511[/C][/ROW]
[ROW][C]Lambda[/C][C]2.38589065989076[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279958&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279958&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)
alpha32.6429898907453
beta-1.38589065989076
S.D.0.316605261909547
T-STAT-4.37734563074542
p-value0.00235715681397511
Lambda2.38589065989076


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')