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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationFri, 12 Dec 2008 04:28:56 -0700
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/Dec/12/t1229081451mk4g7ijnruie7th.htm/, Retrieved Sun, 19 May 2024 05:58:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32569, Retrieved Sun, 19 May 2024 05:58:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact217

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] [Uitvoer.Nederland] [2008-12-03 15:11:10] [988ab43f527fc78aae41c84649095267]
-   P   [Univariate Data Series] [Export From Belgi...] [2008-12-03 15:52:29] [988ab43f527fc78aae41c84649095267]
- RMP     [Standard Deviation-Mean Plot] [standard deviatio...] [2008-12-03 16:25:18] [988ab43f527fc78aae41c84649095267]
-   PD      [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-11 17:25:17] [988ab43f527fc78aae41c84649095267]
-    D          [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-12 11:28:56] [5d823194959040fa9b19b8c8302177e6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
156.3
151.5
159.1
166.9
160.5
162.8
178.9
148.5
184.1
197
186.8
139.2
162.7
187.5
235.8
219.4
212.4
220.2
197.5
185.6
232.4
223.8
219.4
191.4
210.4
212.6
274.4
256
227.6
261.7
237
234.9
310.6
274.2
288.1
242.5
271.7
282.2
317.4
280.3
322.6
328.2
280.7
288.8
347.9
360.1
348
275.7
332.6
340.8
390.5
351.2
377.4
413.5
366.9
364.8
388
429.8
423.6
326.4

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32569&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32569&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32569&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
1165.96666666666717.334638645489557.8
2207.34166666666722.157841145798173.1
3252.530.6368761759123100.2
4308.63333333333332.360198148998288.4
5375.45833333333334.8048966861465103.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 165.966666666667 & 17.3346386454895 & 57.8 \tabularnewline
2 & 207.341666666667 & 22.1578411457981 & 73.1 \tabularnewline
3 & 252.5 & 30.6368761759123 & 100.2 \tabularnewline
4 & 308.633333333333 & 32.3601981489982 & 88.4 \tabularnewline
5 & 375.458333333333 & 34.8048966861465 & 103.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32569&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]165.966666666667[/C][C]17.3346386454895[/C][C]57.8[/C][/ROW]
[ROW][C]2[/C][C]207.341666666667[/C][C]22.1578411457981[/C][C]73.1[/C][/ROW]
[ROW][C]3[/C][C]252.5[/C][C]30.6368761759123[/C][C]100.2[/C][/ROW]
[ROW][C]4[/C][C]308.633333333333[/C][C]32.3601981489982[/C][C]88.4[/C][/ROW]
[ROW][C]5[/C][C]375.458333333333[/C][C]34.8048966861465[/C][C]103.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32569&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32569&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
1165.96666666666717.334638645489557.8
2207.34166666666722.157841145798173.1
3252.530.6368761759123100.2
4308.63333333333332.360198148998288.4
5375.45833333333334.8048966861465103.4






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5.48466980246326
beta0.0838774729292528
S.D.0.0178993174312623
T-STAT4.68607103323144
p-value0.0183680276693928

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5.48466980246326 \tabularnewline
beta & 0.0838774729292528 \tabularnewline
S.D. & 0.0178993174312623 \tabularnewline
T-STAT & 4.68607103323144 \tabularnewline
p-value & 0.0183680276693928 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32569&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.48466980246326[/C][/ROW]
[ROW][C]beta[/C][C]0.0838774729292528[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0178993174312623[/C][/ROW]
[ROW][C]T-STAT[/C][C]4.68607103323144[/C][/ROW]
[ROW][C]p-value[/C][C]0.0183680276693928[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32569&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32569&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)
alpha5.48466980246326
beta0.0838774729292528
S.D.0.0178993174312623
T-STAT4.68607103323144
p-value0.0183680276693928






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-1.56622829767342
beta0.876729407793529
S.D.0.156496289003439
T-STAT5.60223768484546
p-value0.0112379124676925
Lambda0.123270592206471

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.56622829767342 \tabularnewline
beta & 0.876729407793529 \tabularnewline
S.D. & 0.156496289003439 \tabularnewline
T-STAT & 5.60223768484546 \tabularnewline
p-value & 0.0112379124676925 \tabularnewline
Lambda & 0.123270592206471 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32569&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.56622829767342[/C][/ROW]
[ROW][C]beta[/C][C]0.876729407793529[/C][/ROW]
[ROW][C]S.D.[/C][C]0.156496289003439[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.60223768484546[/C][/ROW]
[ROW][C]p-value[/C][C]0.0112379124676925[/C][/ROW]
[ROW][C]Lambda[/C][C]0.123270592206471[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32569&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32569&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-1.56622829767342
beta0.876729407793529
S.D.0.156496289003439
T-STAT5.60223768484546
p-value0.0112379124676925
Lambda0.123270592206471


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')