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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 computationMon, 22 Dec 2008 04:11:05 -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/22/t122994431588r0d8gfxpmk4b5.htm/, Retrieved Mon, 13 May 2024 08:26:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35999, Retrieved Mon, 13 May 2024 08:26:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact216

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- R PD  [Univariate Data Series] [Tijdreeks 2 Buite...] [2008-12-11 16:25:30] [2d4aec5ed1856c4828162be37be304d9]
- RMP     [Central Tendency] [Central tendency ...] [2008-12-11 17:41:16] [2d4aec5ed1856c4828162be37be304d9]
- RMP       [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-12 08:14:08] [2d4aec5ed1856c4828162be37be304d9]
- RMP         [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-12-12 08:45:26] [2d4aec5ed1856c4828162be37be304d9]
- RMP           [Standard Deviation-Mean Plot] [SD Mean Plot Tijd...] [2008-12-12 09:35:09] [2d4aec5ed1856c4828162be37be304d9]
-    D              [Standard Deviation-Mean Plot] [SD Mean Plot Xt] [2008-12-22 11:11:05] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16283,6
16726,5
14968,9
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
21211,2
21423,1
21688,7
23243,2
21490,2
22925,8
23184,8
18562,2

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35999&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35999&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35999&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'Gwilym Jenkins' @ 72.249.127.135






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
115840.20833333331254.602415442174037.4
217212.71666666671133.290074263533981.9
318380.3251356.146188234754907
419348.99166666671177.691521161274007.2
521187.04166666671721.303674258315365.8

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 15840.2083333333 & 1254.60241544217 & 4037.4 \tabularnewline
2 & 17212.7166666667 & 1133.29007426353 & 3981.9 \tabularnewline
3 & 18380.325 & 1356.14618823475 & 4907 \tabularnewline
4 & 19348.9916666667 & 1177.69152116127 & 4007.2 \tabularnewline
5 & 21187.0416666667 & 1721.30367425831 & 5365.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35999&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]15840.2083333333[/C][C]1254.60241544217[/C][C]4037.4[/C][/ROW]
[ROW][C]2[/C][C]17212.7166666667[/C][C]1133.29007426353[/C][C]3981.9[/C][/ROW]
[ROW][C]3[/C][C]18380.325[/C][C]1356.14618823475[/C][C]4907[/C][/ROW]
[ROW][C]4[/C][C]19348.9916666667[/C][C]1177.69152116127[/C][C]4007.2[/C][/ROW]
[ROW][C]5[/C][C]21187.0416666667[/C][C]1721.30367425831[/C][C]5365.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35999&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35999&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
115840.20833333331254.602415442174037.4
217212.71666666671133.290074263533981.9
318380.3251356.146188234754907
419348.99166666671177.691521161274007.2
521187.04166666671721.303674258315365.8






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-188.902190728177
beta0.0825008584605431
S.D.0.0465640857029204
T-STAT1.77177017899374
p-value0.174555489356083

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -188.902190728177 \tabularnewline
beta & 0.0825008584605431 \tabularnewline
S.D. & 0.0465640857029204 \tabularnewline
T-STAT & 1.77177017899374 \tabularnewline
p-value & 0.174555489356083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35999&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-188.902190728177[/C][/ROW]
[ROW][C]beta[/C][C]0.0825008584605431[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0465640857029204[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.77177017899374[/C][/ROW]
[ROW][C]p-value[/C][C]0.174555489356083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35999&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35999&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)
alpha-188.902190728177
beta0.0825008584605431
S.D.0.0465640857029204
T-STAT1.77177017899374
p-value0.174555489356083






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-2.66502016794652
beta1.00311403024156
S.D.0.640097112062451
T-STAT1.56712788003282
p-value0.215074574875112
Lambda-0.00311403024155732

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -2.66502016794652 \tabularnewline
beta & 1.00311403024156 \tabularnewline
S.D. & 0.640097112062451 \tabularnewline
T-STAT & 1.56712788003282 \tabularnewline
p-value & 0.215074574875112 \tabularnewline
Lambda & -0.00311403024155732 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35999&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-2.66502016794652[/C][/ROW]
[ROW][C]beta[/C][C]1.00311403024156[/C][/ROW]
[ROW][C]S.D.[/C][C]0.640097112062451[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.56712788003282[/C][/ROW]
[ROW][C]p-value[/C][C]0.215074574875112[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.00311403024155732[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35999&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35999&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-2.66502016794652
beta1.00311403024156
S.D.0.640097112062451
T-STAT1.56712788003282
p-value0.215074574875112
Lambda-0.00311403024155732


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')