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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 computationMon, 07 Aug 2017 16:32:25 +0200
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/Aug/07/t15021166973z92e0139dhksvc.htm/, Retrieved Sun, 12 May 2024 06:08:19 +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 06:08:19 +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 
3221816
3209817
3197649
3172468
3421574
3408392
3221816
3097770
3109769
3109769
3123120
3147118
3184467
3184467
3160469
3097770
3421574
3470922
3396393
3221816
3296514
3184467
3234998
3259165
3284346
3221816
3234998
3147118
3421574
3508271
3433742
3296514
3445741
3284346
3433742
3421574
3458923
3321695
3470922
3458923
3682848
3632317
3433742
3333694
3470922
3284346
3421574
3445741
3496272
3384394
3445741
3483090
3620318
3508271
3359044
3197649
3347045
2936375
3135119
3246997
3359044
3197649
3197649
3197649
3284346
3160469
2997891
2861846
2960542
2575222
2811315
2948543
2973724
2836496
2848495
2811315
2936375
2848495
2675270
2550041
2761798
2301949
2600572
2736617
2736617
2575222
2425995
2413996
2550041
2425995
2190071
2027493
2202070
1791569
2164721
2363296
2425995
2288767
2115373
2239419
2288767
2251418
1878097
1704872
1828749
1455597
1840917
1978145
2090023
1903447
1728870
1828749
1878097
1779401
1406249
1243671
1392898
982397
1430247
1704872

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






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=&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=&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
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=&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=&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)
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=&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=&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)
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 = 12greygrey0.010.10,010,010,010,10,10,10,010,010,010,010,112DefaultDefaultDefault486060121212 ; par2 = nono0.990.90,990,990,990,990,990,990,990,990,990,990,99grey111111 ; par3 = 0.010.10,010,010,010,10,10,10,010,10,10,10,1FALSE000001 ; par4 = Unknown000000 ; par5 = 121212121212 ; par6 = White NoiseWhite NoiseWhite NoiseWhite NoiseWhite NoiseWhite Noise ; par7 = 0.950.950.950.950.950.95 ; par8 = 480 ;
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')