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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, 01 Aug 2016 13:34:50 +0100

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/2016/Aug/01/t147005496010urqgoz3fss4dp.htm/, Retrieved Mon, 29 Apr 2024 08:20:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295993, Retrieved Mon, 29 Apr 2024 08:20:09 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

162

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

-       [Standard Deviation-Mean Plot] [] [2016-08-01 12:34:50] [b94c13d84d922b33c8d74b1e5b1d38c1] [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=295993&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=295993&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295993&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	744.166666666667	72.9206708857251	210
2	727.5	94.4962721727448	310
3	710	122.77103596829	490
4	700	164.593162345552	620
5	698.333333333333	145.654219009102	540
6	704.166666666667	157.044193741376	600
7	699.166666666667	170.585000583997	620
8	715.833333333333	172.598237288657	590
9	718.333333333333	202.925572264286	700

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 744.166666666667 & 72.9206708857251 & 210 \tabularnewline
2 & 727.5 & 94.4962721727448 & 310 \tabularnewline
3 & 710 & 122.77103596829 & 490 \tabularnewline
4 & 700 & 164.593162345552 & 620 \tabularnewline
5 & 698.333333333333 & 145.654219009102 & 540 \tabularnewline
6 & 704.166666666667 & 157.044193741376 & 600 \tabularnewline
7 & 699.166666666667 & 170.585000583997 & 620 \tabularnewline
8 & 715.833333333333 & 172.598237288657 & 590 \tabularnewline
9 & 718.333333333333 & 202.925572264286 & 700 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295993&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]744.166666666667[/C][C]72.9206708857251[/C][C]210[/C][/ROW]
[ROW][C]2[/C][C]727.5[/C][C]94.4962721727448[/C][C]310[/C][/ROW]
[ROW][C]3[/C][C]710[/C][C]122.77103596829[/C][C]490[/C][/ROW]
[ROW][C]4[/C][C]700[/C][C]164.593162345552[/C][C]620[/C][/ROW]
[ROW][C]5[/C][C]698.333333333333[/C][C]145.654219009102[/C][C]540[/C][/ROW]
[ROW][C]6[/C][C]704.166666666667[/C][C]157.044193741376[/C][C]600[/C][/ROW]
[ROW][C]7[/C][C]699.166666666667[/C][C]170.585000583997[/C][C]620[/C][/ROW]
[ROW][C]8[/C][C]715.833333333333[/C][C]172.598237288657[/C][C]590[/C][/ROW]
[ROW][C]9[/C][C]718.333333333333[/C][C]202.925572264286[/C][C]700[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295993&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295993&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	744.166666666667	72.9206708857251	210
2	727.5	94.4962721727448	310
3	710	122.77103596829	490
4	700	164.593162345552	620
5	698.333333333333	145.654219009102	540
6	704.166666666667	157.044193741376	600
7	699.166666666667	170.585000583997	620
8	715.833333333333	172.598237288657	590
9	718.333333333333	202.925572264286	700

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1376.96611105585
beta	-1.72794805379711
S.D.	0.775952127687301
T-STAT	-2.22687456112428
p-value	0.061252704981263

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1376.96611105585 \tabularnewline
beta & -1.72794805379711 \tabularnewline
S.D. & 0.775952127687301 \tabularnewline
T-STAT & -2.22687456112428 \tabularnewline
p-value & 0.061252704981263 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295993&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1376.96611105585[/C][/ROW]
[ROW][C]beta[/C][C]-1.72794805379711[/C][/ROW]
[ROW][C]S.D.[/C][C]0.775952127687301[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.22687456112428[/C][/ROW]
[ROW][C]p-value[/C][C]0.061252704981263[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295993&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295993&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	1376.96611105585
beta	-1.72794805379711
S.D.	0.775952127687301
T-STAT	-2.22687456112428
p-value	0.061252704981263

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	78.6500407167264
beta	-11.2214248064541
S.D.	3.9671205225793
T-STAT	-2.82860698145826
p-value	0.025456994548278
Lambda	12.2214248064541

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 78.6500407167264 \tabularnewline
beta & -11.2214248064541 \tabularnewline
S.D. & 3.9671205225793 \tabularnewline
T-STAT & -2.82860698145826 \tabularnewline
p-value & 0.025456994548278 \tabularnewline
Lambda & 12.2214248064541 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295993&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]78.6500407167264[/C][/ROW]
[ROW][C]beta[/C][C]-11.2214248064541[/C][/ROW]
[ROW][C]S.D.[/C][C]3.9671205225793[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.82860698145826[/C][/ROW]
[ROW][C]p-value[/C][C]0.025456994548278[/C][/ROW]
[ROW][C]Lambda[/C][C]12.2214248064541[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295993&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295993&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	78.6500407167264
beta	-11.2214248064541
S.D.	3.9671205225793
T-STAT	-2.82860698145826
p-value	0.025456994548278
Lambda	12.2214248064541

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