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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

Thu, 09 Aug 2012 08:41:26 -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/Aug/09/t1344516116zewfqzzqwicvyfs.htm/, Retrieved Wed, 01 May 2024 19:58:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=169174, Retrieved Wed, 01 May 2024 19:58:49 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

139

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

-       [Standard Deviation-Mean Plot] [] [2012-08-09 12:41:26] [d41d8cd98f00b204e9800998ecf8427e] [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=169174&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=169174&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169174&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	905	42.9587540025842	120
2	884.166666666667	77.1607923675482	250
3	877.5	92.1584603722405	280
4	905.833333333333	90.900378370383	300
5	904.166666666667	86.5981664023114	270
6	883.333333333333	96.13752775282	300
7	878.333333333333	104.083299973307	350
8	889.166666666667	102.021239618686	340
9	887.5	83.0251878539387	270

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 905 & 42.9587540025842 & 120 \tabularnewline
2 & 884.166666666667 & 77.1607923675482 & 250 \tabularnewline
3 & 877.5 & 92.1584603722405 & 280 \tabularnewline
4 & 905.833333333333 & 90.900378370383 & 300 \tabularnewline
5 & 904.166666666667 & 86.5981664023114 & 270 \tabularnewline
6 & 883.333333333333 & 96.13752775282 & 300 \tabularnewline
7 & 878.333333333333 & 104.083299973307 & 350 \tabularnewline
8 & 889.166666666667 & 102.021239618686 & 340 \tabularnewline
9 & 887.5 & 83.0251878539387 & 270 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169174&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]905[/C][C]42.9587540025842[/C][C]120[/C][/ROW]
[ROW][C]2[/C][C]884.166666666667[/C][C]77.1607923675482[/C][C]250[/C][/ROW]
[ROW][C]3[/C][C]877.5[/C][C]92.1584603722405[/C][C]280[/C][/ROW]
[ROW][C]4[/C][C]905.833333333333[/C][C]90.900378370383[/C][C]300[/C][/ROW]
[ROW][C]5[/C][C]904.166666666667[/C][C]86.5981664023114[/C][C]270[/C][/ROW]
[ROW][C]6[/C][C]883.333333333333[/C][C]96.13752775282[/C][C]300[/C][/ROW]
[ROW][C]7[/C][C]878.333333333333[/C][C]104.083299973307[/C][C]350[/C][/ROW]
[ROW][C]8[/C][C]889.166666666667[/C][C]102.021239618686[/C][C]340[/C][/ROW]
[ROW][C]9[/C][C]887.5[/C][C]83.0251878539387[/C][C]270[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169174&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169174&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	905	42.9587540025842	120
2	884.166666666667	77.1607923675482	250
3	877.5	92.1584603722405	280
4	905.833333333333	90.900378370383	300
5	904.166666666667	86.5981664023114	270
6	883.333333333333	96.13752775282	300
7	878.333333333333	104.083299973307	350
8	889.166666666667	102.021239618686	340
9	887.5	83.0251878539387	270

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	823.049847745697
beta	-0.827499042170612
S.D.	0.517137450209238
T-STAT	-1.60015299962476
p-value	0.153597847849156

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 823.049847745697 \tabularnewline
beta & -0.827499042170612 \tabularnewline
S.D. & 0.517137450209238 \tabularnewline
T-STAT & -1.60015299962476 \tabularnewline
p-value & 0.153597847849156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169174&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]823.049847745697[/C][/ROW]
[ROW][C]beta[/C][C]-0.827499042170612[/C][/ROW]
[ROW][C]S.D.[/C][C]0.517137450209238[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.60015299962476[/C][/ROW]
[ROW][C]p-value[/C][C]0.153597847849156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169174&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169174&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	823.049847745697
beta	-0.827499042170612
S.D.	0.517137450209238
T-STAT	-1.60015299962476
p-value	0.153597847849156

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	76.8285917775368
beta	-10.6599792892206
S.D.	6.7804194624382
T-STAT	-1.5721710652673
p-value	0.159906974605227
Lambda	11.6599792892206

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 76.8285917775368 \tabularnewline
beta & -10.6599792892206 \tabularnewline
S.D. & 6.7804194624382 \tabularnewline
T-STAT & -1.5721710652673 \tabularnewline
p-value & 0.159906974605227 \tabularnewline
Lambda & 11.6599792892206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=169174&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]76.8285917775368[/C][/ROW]
[ROW][C]beta[/C][C]-10.6599792892206[/C][/ROW]
[ROW][C]S.D.[/C][C]6.7804194624382[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.5721710652673[/C][/ROW]
[ROW][C]p-value[/C][C]0.159906974605227[/C][/ROW]
[ROW][C]Lambda[/C][C]11.6599792892206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=169174&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=169174&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	76.8285917775368
beta	-10.6599792892206
S.D.	6.7804194624382
T-STAT	-1.5721710652673
p-value	0.159906974605227
Lambda	11.6599792892206

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