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Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Sun, 25 Nov 2007 02:54:47 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/25/t1195983972f9cvxv2lrkwkjsl.htm/, Retrieved Sat, 04 May 2024 11:17:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6388, Retrieved Sat, 04 May 2024 11:17:15 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

238

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Standard Deviation-Mean Plot] [SDMP Bouwnijverheid] [2007-11-25 09:54:47] [52b0ae29b3b0ac57b71db95ac12f6d2e] [Current]

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Boxplots

Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6388&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6388&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6388&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	93.2666666666667	16.2603440270736	19.5
2	89.175	17.3885607643228	63.3
3	88.7416666666667	17.9595737109428	3.8
4	92.35	18.4053598912728	23.9
5	93.0166666666667	16.0850485817976	25.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 93.2666666666667 & 16.2603440270736 & 19.5 \tabularnewline
2 & 89.175 & 17.3885607643228 & 63.3 \tabularnewline
3 & 88.7416666666667 & 17.9595737109428 & 3.8 \tabularnewline
4 & 92.35 & 18.4053598912728 & 23.9 \tabularnewline
5 & 93.0166666666667 & 16.0850485817976 & 25.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6388&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]93.2666666666667[/C][C]16.2603440270736[/C][C]19.5[/C][/ROW]
[ROW][C]2[/C][C]89.175[/C][C]17.3885607643228[/C][C]63.3[/C][/ROW]
[ROW][C]3[/C][C]88.7416666666667[/C][C]17.9595737109428[/C][C]3.8[/C][/ROW]
[ROW][C]4[/C][C]92.35[/C][C]18.4053598912728[/C][C]23.9[/C][/ROW]
[ROW][C]5[/C][C]93.0166666666667[/C][C]16.0850485817976[/C][C]25.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6388&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6388&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	93.2666666666667	16.2603440270736	19.5
2	89.175	17.3885607643228	63.3
3	88.7416666666667	17.9595737109428	3.8
4	92.35	18.4053598912728	23.9
5	93.0166666666667	16.0850485817976	25.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	40.5136626793137
beta	-0.255107713111727
S.D.	0.227803421891503
T-STAT	-1.11985900384424
p-value	0.344346933910393

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 40.5136626793137 \tabularnewline
beta & -0.255107713111727 \tabularnewline
S.D. & 0.227803421891503 \tabularnewline
T-STAT & -1.11985900384424 \tabularnewline
p-value & 0.344346933910393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6388&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]40.5136626793137[/C][/ROW]
[ROW][C]beta[/C][C]-0.255107713111727[/C][/ROW]
[ROW][C]S.D.[/C][C]0.227803421891503[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.11985900384424[/C][/ROW]
[ROW][C]p-value[/C][C]0.344346933910393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6388&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6388&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	40.5136626793137
beta	-0.255107713111727
S.D.	0.227803421891503
T-STAT	-1.11985900384424
p-value	0.344346933910393

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	9.05485878723518
beta	-1.37575897656202
S.D.	1.19805303866367
T-STAT	-1.14832894050881
p-value	0.334093936505390
Lambda	2.37575897656202

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 9.05485878723518 \tabularnewline
beta & -1.37575897656202 \tabularnewline
S.D. & 1.19805303866367 \tabularnewline
T-STAT & -1.14832894050881 \tabularnewline
p-value & 0.334093936505390 \tabularnewline
Lambda & 2.37575897656202 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6388&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]9.05485878723518[/C][/ROW]
[ROW][C]beta[/C][C]-1.37575897656202[/C][/ROW]
[ROW][C]S.D.[/C][C]1.19805303866367[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.14832894050881[/C][/ROW]
[ROW][C]p-value[/C][C]0.334093936505390[/C][/ROW]
[ROW][C]Lambda[/C][C]2.37575897656202[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6388&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6388&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	9.05485878723518
beta	-1.37575897656202
S.D.	1.19805303866367
T-STAT	-1.14832894050881
p-value	0.334093936505390
Lambda	2.37575897656202

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code