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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

Mon, 30 Apr 2012 05:57:39 -0400

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/2012/Apr/30/t13357798797dqarmsxx9zkqgy.htm/, Retrieved Mon, 29 Apr 2024 03:46:03 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=165204, Retrieved Mon, 29 Apr 2024 03:46:03 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

159

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

-       [Standard Deviation-Mean Plot] [] [2012-04-30 09:57:39] [30c94b4dfb4338ed9c3f059abdec5f3e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165204&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165204&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165204&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 computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	99.9108333333333	2.21526299827248	4.59
2	102.3175	0.571570802104325	1.11
3	103.386666666667	2.12150604024308	4.12
4	105.24	0.679705818718661	1.32000000000001
5	105.705	0.896401898501093	2.14

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 99.9108333333333 & 2.21526299827248 & 4.59 \tabularnewline
2 & 102.3175 & 0.571570802104325 & 1.11 \tabularnewline
3 & 103.386666666667 & 2.12150604024308 & 4.12 \tabularnewline
4 & 105.24 & 0.679705818718661 & 1.32000000000001 \tabularnewline
5 & 105.705 & 0.896401898501093 & 2.14 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165204&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]99.9108333333333[/C][C]2.21526299827248[/C][C]4.59[/C][/ROW]
[ROW][C]2[/C][C]102.3175[/C][C]0.571570802104325[/C][C]1.11[/C][/ROW]
[ROW][C]3[/C][C]103.386666666667[/C][C]2.12150604024308[/C][C]4.12[/C][/ROW]
[ROW][C]4[/C][C]105.24[/C][C]0.679705818718661[/C][C]1.32000000000001[/C][/ROW]
[ROW][C]5[/C][C]105.705[/C][C]0.896401898501093[/C][C]2.14[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165204&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165204&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	99.9108333333333	2.21526299827248	4.59
2	102.3175	0.571570802104325	1.11
3	103.386666666667	2.12150604024308	4.12
4	105.24	0.679705818718661	1.32000000000001
5	105.705	0.896401898501093	2.14

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	22.3710266736769
beta	-0.203985375968996
S.D.	0.159290474804274
T-STAT	-1.2805874062441
p-value	0.29036959310661

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 22.3710266736769 \tabularnewline
beta & -0.203985375968996 \tabularnewline
S.D. & 0.159290474804274 \tabularnewline
T-STAT & -1.2805874062441 \tabularnewline
p-value & 0.29036959310661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165204&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22.3710266736769[/C][/ROW]
[ROW][C]beta[/C][C]-0.203985375968996[/C][/ROW]
[ROW][C]S.D.[/C][C]0.159290474804274[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.2805874062441[/C][/ROW]
[ROW][C]p-value[/C][C]0.29036959310661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165204&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165204&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	22.3710266736769
beta	-0.203985375968996
S.D.	0.159290474804274
T-STAT	-1.2805874062441
p-value	0.29036959310661

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	67.4370476794546
beta	-14.5202899238779
S.D.	13.7782114609802
T-STAT	-1.0538588382824
p-value	0.369325907221918
Lambda	15.5202899238779

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 67.4370476794546 \tabularnewline
beta & -14.5202899238779 \tabularnewline
S.D. & 13.7782114609802 \tabularnewline
T-STAT & -1.0538588382824 \tabularnewline
p-value & 0.369325907221918 \tabularnewline
Lambda & 15.5202899238779 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=165204&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]67.4370476794546[/C][/ROW]
[ROW][C]beta[/C][C]-14.5202899238779[/C][/ROW]
[ROW][C]S.D.[/C][C]13.7782114609802[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.0538588382824[/C][/ROW]
[ROW][C]p-value[/C][C]0.369325907221918[/C][/ROW]
[ROW][C]Lambda[/C][C]15.5202899238779[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=165204&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=165204&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	67.4370476794546
beta	-14.5202899238779
S.D.	13.7782114609802
T-STAT	-1.0538588382824
p-value	0.369325907221918
Lambda	15.5202899238779

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

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code