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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 computationWed, 03 Dec 2008 08:38:01 -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/03/t1228318738c3ifk5mcf13t895.htm/, Retrieved Tue, 21 May 2024 02:22:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28741, Retrieved Tue, 21 May 2024 02:22:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

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] [totale uitvoer be...] [2008-11-27 20:32:52] [1e1d8320a8a1170c475bf6e4ce119de6]
-   P   [Univariate Data Series] [totale uitvoer be...] [2008-11-27 20:35:12] [1e1d8320a8a1170c475bf6e4ce119de6]
- RMP       [Standard Deviation-Mean Plot] [SDM plot total ex...] [2008-12-03 15:38:01] [fdd69703d301fae09456f660b2f52997] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13807.9
14101.7
16010.3
14633.1
14478.5
15327.3
14179.5
11398.2
16111.5
15887.4
14529.3
13923.1
13960.2
14807.8
17511.5
15845.9
14594.2
17252.2
14832.8
13132.1
17665.9
16913
17318.8
16224.2
15469.6
16557.5
19414.8
17335
16525.2
18160.4
15553.8
15262.2
18581
17564.1
18948.6
17187.8
17564.8
17668.4
20811.7
17257.8
18984.2
20532.6
17082.3
16894.9
20274.9
20078.6
19900.9
17012.2
19642.9
19024
21691
18835.9
19873.4
21468.2
19406.8
18385.3
20739.3
22268.3
21569
17514.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28741&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28741&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28741&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
114532.31666666671285.870371547714713.3
215838.21666666671540.548703802604533.8
317213.33333333331390.512273381384152.6
418671.94166666671562.889439734413916.8
520034.90833333331499.714932583914753.5

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 14532.3166666667 & 1285.87037154771 & 4713.3 \tabularnewline
2 & 15838.2166666667 & 1540.54870380260 & 4533.8 \tabularnewline
3 & 17213.3333333333 & 1390.51227338138 & 4152.6 \tabularnewline
4 & 18671.9416666667 & 1562.88943973441 & 3916.8 \tabularnewline
5 & 20034.9083333333 & 1499.71493258391 & 4753.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28741&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]14532.3166666667[/C][C]1285.87037154771[/C][C]4713.3[/C][/ROW]
[ROW][C]2[/C][C]15838.2166666667[/C][C]1540.54870380260[/C][C]4533.8[/C][/ROW]
[ROW][C]3[/C][C]17213.3333333333[/C][C]1390.51227338138[/C][C]4152.6[/C][/ROW]
[ROW][C]4[/C][C]18671.9416666667[/C][C]1562.88943973441[/C][C]3916.8[/C][/ROW]
[ROW][C]5[/C][C]20034.9083333333[/C][C]1499.71493258391[/C][C]4753.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28741&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28741&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
114532.31666666671285.870371547714713.3
215838.21666666671540.548703802604533.8
317213.33333333331390.512273381384152.6
418671.94166666671562.889439734413916.8
520034.90833333331499.714932583914753.5






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha898.161214844218
beta0.0323178408356663
S.D.0.0242180353344673
T-STAT1.33445345129509
p-value0.274300558600403

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 898.161214844218 \tabularnewline
beta & 0.0323178408356663 \tabularnewline
S.D. & 0.0242180353344673 \tabularnewline
T-STAT & 1.33445345129509 \tabularnewline
p-value & 0.274300558600403 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28741&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]898.161214844218[/C][/ROW]
[ROW][C]beta[/C][C]0.0323178408356663[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0242180353344673[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.33445345129509[/C][/ROW]
[ROW][C]p-value[/C][C]0.274300558600403[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28741&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28741&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)
alpha898.161214844218
beta0.0323178408356663
S.D.0.0242180353344673
T-STAT1.33445345129509
p-value0.274300558600403






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.31104902057289
beta0.407169263835276
S.D.0.284223923660629
T-STAT1.43256506556938
p-value0.247409104910073
Lambda0.592830736164724

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.31104902057289 \tabularnewline
beta & 0.407169263835276 \tabularnewline
S.D. & 0.284223923660629 \tabularnewline
T-STAT & 1.43256506556938 \tabularnewline
p-value & 0.247409104910073 \tabularnewline
Lambda & 0.592830736164724 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28741&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.31104902057289[/C][/ROW]
[ROW][C]beta[/C][C]0.407169263835276[/C][/ROW]
[ROW][C]S.D.[/C][C]0.284223923660629[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.43256506556938[/C][/ROW]
[ROW][C]p-value[/C][C]0.247409104910073[/C][/ROW]
[ROW][C]Lambda[/C][C]0.592830736164724[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28741&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28741&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)
alpha3.31104902057289
beta0.407169263835276
S.D.0.284223923660629
T-STAT1.43256506556938
p-value0.247409104910073
Lambda0.592830736164724


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')