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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, 29 Dec 2010 21:39:07 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t1293658614vm2j540g6t6lxwz.htm/, Retrieved Fri, 03 May 2024 06:30:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=117133, Retrieved Fri, 03 May 2024 06:30:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [] [2010-12-26 11:42:34] [a2638725f7f7c6bd63902ba17eba666b]
-         [Standard Deviation-Mean Plot] [Standard Deviatio...] [2010-12-29 21:39:07] [d7e71f84f972bd09532f49e6d8781449] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16896.2
16698
19691.6
15930.7
17444.6
17699.4
15189.8
15672.7
17180.8
17664.9
17862.9
16162.3
17463.6
16772.1
19106.9
16721.3
18161.3
18509.9
17802.7
16409.9
17967.7
20286.6
19537.3
18021.9
20194.3
19049.6
20244.7
21473.3
19673.6
21053.2
20159.5
18203.6
21289.5
20432.3
17180.4
15816.8
15076.6
14531.6
15761.3
14345.5
13916.8
15496.8
14285.6
13597.3
16263.1
16773.3
15986.9
16842.6
16014.6
15878.6
18664.9
17690.5
17107.6
19165.7
17203.6
16579
18885.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org

\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 & 0 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ www.yougetit.org \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117133&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ www.yougetit.org[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117133&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117133&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 time0 seconds
R Server'Herman Ole Andreas Wold' @ www.yougetit.org






Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
117007.8251211.154742853434501.8
218063.43333333331169.856011600913876.7
319564.23333333331723.106415926215656.5
415239.78333333331109.893094633513245.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 17007.825 & 1211.15474285343 & 4501.8 \tabularnewline
2 & 18063.4333333333 & 1169.85601160091 & 3876.7 \tabularnewline
3 & 19564.2333333333 & 1723.10641592621 & 5656.5 \tabularnewline
4 & 15239.7833333333 & 1109.89309463351 & 3245.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117133&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]17007.825[/C][C]1211.15474285343[/C][C]4501.8[/C][/ROW]
[ROW][C]2[/C][C]18063.4333333333[/C][C]1169.85601160091[/C][C]3876.7[/C][/ROW]
[ROW][C]3[/C][C]19564.2333333333[/C][C]1723.10641592621[/C][C]5656.5[/C][/ROW]
[ROW][C]4[/C][C]15239.7833333333[/C][C]1109.89309463351[/C][C]3245.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117133&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117133&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
117007.8251211.154742853434501.8
218063.43333333331169.856011600913876.7
319564.23333333331723.106415926215656.5
415239.78333333331109.893094633513245.3






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-938.58402411968
beta0.128347922229899
S.D.0.0620532115186417
T-STAT2.06835261364903
p-value0.174511420907379

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -938.58402411968 \tabularnewline
beta & 0.128347922229899 \tabularnewline
S.D. & 0.0620532115186417 \tabularnewline
T-STAT & 2.06835261364903 \tabularnewline
p-value & 0.174511420907379 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117133&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-938.58402411968[/C][/ROW]
[ROW][C]beta[/C][C]0.128347922229899[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0620532115186417[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.06835261364903[/C][/ROW]
[ROW][C]p-value[/C][C]0.174511420907379[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117133&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117133&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-938.58402411968
beta0.128347922229899
S.D.0.0620532115186417
T-STAT2.06835261364903
p-value0.174511420907379






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-8.01609478832241
beta1.55397229493452
S.D.0.771596388383492
T-STAT2.01397041034643
p-value0.181615494973601
Lambda-0.553972294934522

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -8.01609478832241 \tabularnewline
beta & 1.55397229493452 \tabularnewline
S.D. & 0.771596388383492 \tabularnewline
T-STAT & 2.01397041034643 \tabularnewline
p-value & 0.181615494973601 \tabularnewline
Lambda & -0.553972294934522 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=117133&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-8.01609478832241[/C][/ROW]
[ROW][C]beta[/C][C]1.55397229493452[/C][/ROW]
[ROW][C]S.D.[/C][C]0.771596388383492[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.01397041034643[/C][/ROW]
[ROW][C]p-value[/C][C]0.181615494973601[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.553972294934522[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=117133&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=117133&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-8.01609478832241
beta1.55397229493452
S.D.0.771596388383492
T-STAT2.01397041034643
p-value0.181615494973601
Lambda-0.553972294934522


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')