FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 26 Nov 2007 10:59:08 -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/2007/Nov/26/t11960994346i7l1tlb936q2d2.htm/, Retrieved Thu, 02 May 2024 17:29:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6599, Retrieved Thu, 02 May 2024 17:29:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192

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] [Opdracht 4 Questi...] [2007-11-26 17:59:08] [cb172450b25aceeff04d58e88e905157] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
20538.6
20667.5
20554.9
19982.3
19636.6
19587.9
19861.1
20164.6
20146.9
20192.8
20361.8
20639.7
21251.5
21313.1
21300.0
20477.3
20128.3
20079.5
20235.9
20444.8
20319.9
20384.9
20506.7
20796.5
21760.2
21971.6
21652.7
20702.7
20379.9
20240.1
20376.5
20680.4
20532.0
20749.2
20900.7
21141.8
21770.2
21792.6
21670.1
20810.5
20647.0
20312.9
20014.2
20491.2
20302.7
20641.0
20475.6
20703.0
21158.6
20866.8
20595.2
19373.1
18675.4
18737.5
18587.6
18798.3
18429.5
18485.1
18597.5
18615.1

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6599&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6599&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6599&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 compuational 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
120194.5583333333373.774031050686128.900000000001
220603.2453.272386500254645.599999999999
320923.9833333333582.450433058211416.70000000000
420802.5833333333606.3597879347232419.5
519243.30833333331018.186895201762483.20000000000

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 20194.5583333333 & 373.774031050686 & 128.900000000001 \tabularnewline
2 & 20603.2 & 453.272386500254 & 645.599999999999 \tabularnewline
3 & 20923.9833333333 & 582.45043305821 & 1416.70000000000 \tabularnewline
4 & 20802.5833333333 & 606.359787934723 & 2419.5 \tabularnewline
5 & 19243.3083333333 & 1018.18689520176 & 2483.20000000000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6599&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]20194.5583333333[/C][C]373.774031050686[/C][C]128.900000000001[/C][/ROW]
[ROW][C]2[/C][C]20603.2[/C][C]453.272386500254[/C][C]645.599999999999[/C][/ROW]
[ROW][C]3[/C][C]20923.9833333333[/C][C]582.45043305821[/C][C]1416.70000000000[/C][/ROW]
[ROW][C]4[/C][C]20802.5833333333[/C][C]606.359787934723[/C][C]2419.5[/C][/ROW]
[ROW][C]5[/C][C]19243.3083333333[/C][C]1018.18689520176[/C][C]2483.20000000000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6599&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6599&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
120194.5583333333373.774031050686128.900000000001
220603.2453.272386500254645.599999999999
320923.9833333333582.450433058211416.70000000000
420802.5833333333606.3597879347232419.5
519243.30833333331018.186895201762483.20000000000






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha5808.55701261132
beta-0.255569876958040
S.D.0.151411553776691
T-STAT-1.68791529168882
p-value0.190011403260197

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 5808.55701261132 \tabularnewline
beta & -0.255569876958040 \tabularnewline
S.D. & 0.151411553776691 \tabularnewline
T-STAT & -1.68791529168882 \tabularnewline
p-value & 0.190011403260197 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6599&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5808.55701261132[/C][/ROW]
[ROW][C]beta[/C][C]-0.255569876958040[/C][/ROW]
[ROW][C]S.D.[/C][C]0.151411553776691[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.68791529168882[/C][/ROW]
[ROW][C]p-value[/C][C]0.190011403260197[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6599&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6599&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)
alpha5808.55701261132
beta-0.255569876958040
S.D.0.151411553776691
T-STAT-1.68791529168882
p-value0.190011403260197






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha71.2675359195801
beta-6.5439293364969
S.D.5.21261914829987
T-STAT-1.25540139233676
p-value0.298217850694004
Lambda7.5439293364969

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 71.2675359195801 \tabularnewline
beta & -6.5439293364969 \tabularnewline
S.D. & 5.21261914829987 \tabularnewline
T-STAT & -1.25540139233676 \tabularnewline
p-value & 0.298217850694004 \tabularnewline
Lambda & 7.5439293364969 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6599&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]71.2675359195801[/C][/ROW]
[ROW][C]beta[/C][C]-6.5439293364969[/C][/ROW]
[ROW][C]S.D.[/C][C]5.21261914829987[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.25540139233676[/C][/ROW]
[ROW][C]p-value[/C][C]0.298217850694004[/C][/ROW]
[ROW][C]Lambda[/C][C]7.5439293364969[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6599&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6599&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)
alpha71.2675359195801
beta-6.5439293364969
S.D.5.21261914829987
T-STAT-1.25540139233676
p-value0.298217850694004
Lambda7.5439293364969


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')