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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

Sat, 21 Nov 2015 12:51:32 +0000

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/2015/Nov/21/t14481103340s3mflacp0uf7yz.htm/, Retrieved Tue, 21 May 2024 22:37:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283768, Retrieved Tue, 21 May 2024 22:37:39 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

114

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

-       [Standard Deviation-Mean Plot] [] [2015-11-21 12:51:32] [5a70237751c59f15349851dd3eb2a645] [Current]

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Boxplots

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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283768&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283768&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283768&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	93.55	1.88143079016524	4.16
2	96.55	0.217088168095992	0.480000000000004
3	96.925	1.32966502958794	2.94
4	99.2425	0.203520157589992	0.450000000000003
5	100.0025	0.76433125850463	1.69
6	101.575	0.587947121926638	1.3

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 93.55 & 1.88143079016524 & 4.16 \tabularnewline
2 & 96.55 & 0.217088168095992 & 0.480000000000004 \tabularnewline
3 & 96.925 & 1.32966502958794 & 2.94 \tabularnewline
4 & 99.2425 & 0.203520157589992 & 0.450000000000003 \tabularnewline
5 & 100.0025 & 0.76433125850463 & 1.69 \tabularnewline
6 & 101.575 & 0.587947121926638 & 1.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283768&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]93.55[/C][C]1.88143079016524[/C][C]4.16[/C][/ROW]
[ROW][C]2[/C][C]96.55[/C][C]0.217088168095992[/C][C]0.480000000000004[/C][/ROW]
[ROW][C]3[/C][C]96.925[/C][C]1.32966502958794[/C][C]2.94[/C][/ROW]
[ROW][C]4[/C][C]99.2425[/C][C]0.203520157589992[/C][C]0.450000000000003[/C][/ROW]
[ROW][C]5[/C][C]100.0025[/C][C]0.76433125850463[/C][C]1.69[/C][/ROW]
[ROW][C]6[/C][C]101.575[/C][C]0.587947121926638[/C][C]1.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283768&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283768&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	93.55	1.88143079016524	4.16
2	96.55	0.217088168095992	0.480000000000004
3	96.925	1.32966502958794	2.94
4	99.2425	0.203520157589992	0.450000000000003
5	100.0025	0.76433125850463	1.69
6	101.575	0.587947121926638	1.3

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	15.2753266564486
beta	-0.147433383651849
S.D.	0.0881501391008094
T-STAT	-1.67252581965007
p-value	0.169737169546821

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 15.2753266564486 \tabularnewline
beta & -0.147433383651849 \tabularnewline
S.D. & 0.0881501391008094 \tabularnewline
T-STAT & -1.67252581965007 \tabularnewline
p-value & 0.169737169546821 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283768&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]15.2753266564486[/C][/ROW]
[ROW][C]beta[/C][C]-0.147433383651849[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0881501391008094[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.67252581965007[/C][/ROW]
[ROW][C]p-value[/C][C]0.169737169546821[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283768&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283768&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	15.2753266564486
beta	-0.147433383651849
S.D.	0.0881501391008094
T-STAT	-1.67252581965007
p-value	0.169737169546821

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	58.6323052510485
beta	-12.8988400973622
S.D.	14.1293386501736
T-STAT	-0.912911808310555
p-value	0.412935264161892
Lambda	13.8988400973622

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 58.6323052510485 \tabularnewline
beta & -12.8988400973622 \tabularnewline
S.D. & 14.1293386501736 \tabularnewline
T-STAT & -0.912911808310555 \tabularnewline
p-value & 0.412935264161892 \tabularnewline
Lambda & 13.8988400973622 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283768&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]58.6323052510485[/C][/ROW]
[ROW][C]beta[/C][C]-12.8988400973622[/C][/ROW]
[ROW][C]S.D.[/C][C]14.1293386501736[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.912911808310555[/C][/ROW]
[ROW][C]p-value[/C][C]0.412935264161892[/C][/ROW]
[ROW][C]Lambda[/C][C]13.8988400973622[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283768&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283768&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	58.6323052510485
beta	-12.8988400973622
S.D.	14.1293386501736
T-STAT	-0.912911808310555
p-value	0.412935264161892
Lambda	13.8988400973622

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