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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, 22 Dec 2010 20:24:16 +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/22/t1293049308p0jw1msyffujs71.htm/, Retrieved Mon, 06 May 2024 03:09:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114560, Retrieved Mon, 06 May 2024 03:09:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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] [mean plot bel20] [2008-12-10 18:16:19] [74be16979710d4c4e7c6647856088456]
-  M D  [Standard Deviation-Mean Plot] [] [2009-12-15 12:36:38] [2f674a53c3d7aaa1bcf80e66074d3c9b]
-    D    [Standard Deviation-Mean Plot] [] [2010-12-22 19:38:36] [82643889efeee0b265cd2ff213e5137b]
-             [Standard Deviation-Mean Plot] [] [2010-12-22 20:24:16] [4afc4ea409ad669ec2851bc39795365d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,300
2,100
9,100
15,800
5,200
10,900
8,300
11,000
3,200
7,600
6,300
8,600
6,600
9,500
4,800
12,000
3,300
11,000
4,700
10,400
7,400
2,100
7,700
17,900
6,100
8,200
8,400
11,900
10,800
13,800
14,300
15,200
10,000
11,900
6,500
7,500
10,600
7,400
8,400
5,700
4,900
3,200
8,100
11,000
4,900
13,200
9,700
12,800

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=114560&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=114560&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114560&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
17.866666666666673.7090389182333613.7
28.116666666666674.3827831202088815.8
310.38333333333333.098044348920599.1
48.3253.240966466405310

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 7.86666666666667 & 3.70903891823336 & 13.7 \tabularnewline
2 & 8.11666666666667 & 4.38278312020888 & 15.8 \tabularnewline
3 & 10.3833333333333 & 3.09804434892059 & 9.1 \tabularnewline
4 & 8.325 & 3.2409664664053 & 10 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114560&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]7.86666666666667[/C][C]3.70903891823336[/C][C]13.7[/C][/ROW]
[ROW][C]2[/C][C]8.11666666666667[/C][C]4.38278312020888[/C][C]15.8[/C][/ROW]
[ROW][C]3[/C][C]10.3833333333333[/C][C]3.09804434892059[/C][C]9.1[/C][/ROW]
[ROW][C]4[/C][C]8.325[/C][C]3.2409664664053[/C][C]10[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114560&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114560&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
17.866666666666673.7090389182333613.7
28.116666666666674.3827831202088815.8
310.38333333333333.098044348920599.1
48.3253.240966466405310






Regression: S.E.(k) = alpha + beta * Mean(k)
alpha6.32902021637594
beta-0.313771261448060
S.D.0.276121449348892
T-STAT-1.13635236301978
p-value0.373632085977456

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.32902021637594 \tabularnewline
beta & -0.313771261448060 \tabularnewline
S.D. & 0.276121449348892 \tabularnewline
T-STAT & -1.13635236301978 \tabularnewline
p-value & 0.373632085977456 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114560&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.32902021637594[/C][/ROW]
[ROW][C]beta[/C][C]-0.313771261448060[/C][/ROW]
[ROW][C]S.D.[/C][C]0.276121449348892[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.13635236301978[/C][/ROW]
[ROW][C]p-value[/C][C]0.373632085977456[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114560&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114560&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)
alpha6.32902021637594
beta-0.313771261448060
S.D.0.276121449348892
T-STAT-1.13635236301978
p-value0.373632085977456






Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha3.0235410962296
beta-0.81233166264898
S.D.0.65796433434932
T-STAT-1.23461351967097
p-value0.342347601353041
Lambda1.81233166264898

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.0235410962296 \tabularnewline
beta & -0.81233166264898 \tabularnewline
S.D. & 0.65796433434932 \tabularnewline
T-STAT & -1.23461351967097 \tabularnewline
p-value & 0.342347601353041 \tabularnewline
Lambda & 1.81233166264898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114560&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.0235410962296[/C][/ROW]
[ROW][C]beta[/C][C]-0.81233166264898[/C][/ROW]
[ROW][C]S.D.[/C][C]0.65796433434932[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.23461351967097[/C][/ROW]
[ROW][C]p-value[/C][C]0.342347601353041[/C][/ROW]
[ROW][C]Lambda[/C][C]1.81233166264898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114560&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114560&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)
alpha3.0235410962296
beta-0.81233166264898
S.D.0.65796433434932
T-STAT-1.23461351967097
p-value0.342347601353041
Lambda1.81233166264898


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')