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Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Wed, 18 Nov 2015 11:11:31 +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/18/t1447845111qbo1j14n3b98i59.htm/, Retrieved Tue, 14 May 2024 01:48:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283481, Retrieved Tue, 14 May 2024 01:48:18 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

136

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

-       [Standard Deviation-Mean Plot] [] [2015-11-18 11:11:31] [4535d628e97572fda841f25b347e529f] [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=283481&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=283481&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283481&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	344.1	2.65832027165025	6.19999999999999
2	352.1	2.53771550808991	6
3	365.075	3.7562170686299	8.89999999999998
4	373.4	3.88243909589491	8.5
5	386.025	4.59664732894167	10.4
6	401.15	4.85832618638698	11.2
7	416.1	5.04116388677588	11.2
8	426.8	3.42928563989645	8.19999999999999
9	438.95	3.92640632979657	9.19999999999999
10	449.075	3.79418414594407	8
11	462.425	3.40036762718386	7.80000000000001
12	473.225	3.81171439993432	8.80000000000001
13	484.25	3.66651514838454	8.5
14	496.95	4.39279713470433	10.2
15	511.875	7.77833529747849	18.3
16	532.075	5.72501819502201	13.3
17	549.9	4.52769256906871	10.5
18	562.7	3.85140666943044	8.89999999999998
19	571.675	2.49582985531198	5.89999999999998
20	581.95	3.9644251369734	9.39999999999998

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 344.1 & 2.65832027165025 & 6.19999999999999 \tabularnewline
2 & 352.1 & 2.53771550808991 & 6 \tabularnewline
3 & 365.075 & 3.7562170686299 & 8.89999999999998 \tabularnewline
4 & 373.4 & 3.88243909589491 & 8.5 \tabularnewline
5 & 386.025 & 4.59664732894167 & 10.4 \tabularnewline
6 & 401.15 & 4.85832618638698 & 11.2 \tabularnewline
7 & 416.1 & 5.04116388677588 & 11.2 \tabularnewline
8 & 426.8 & 3.42928563989645 & 8.19999999999999 \tabularnewline
9 & 438.95 & 3.92640632979657 & 9.19999999999999 \tabularnewline
10 & 449.075 & 3.79418414594407 & 8 \tabularnewline
11 & 462.425 & 3.40036762718386 & 7.80000000000001 \tabularnewline
12 & 473.225 & 3.81171439993432 & 8.80000000000001 \tabularnewline
13 & 484.25 & 3.66651514838454 & 8.5 \tabularnewline
14 & 496.95 & 4.39279713470433 & 10.2 \tabularnewline
15 & 511.875 & 7.77833529747849 & 18.3 \tabularnewline
16 & 532.075 & 5.72501819502201 & 13.3 \tabularnewline
17 & 549.9 & 4.52769256906871 & 10.5 \tabularnewline
18 & 562.7 & 3.85140666943044 & 8.89999999999998 \tabularnewline
19 & 571.675 & 2.49582985531198 & 5.89999999999998 \tabularnewline
20 & 581.95 & 3.9644251369734 & 9.39999999999998 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283481&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]344.1[/C][C]2.65832027165025[/C][C]6.19999999999999[/C][/ROW]
[ROW][C]2[/C][C]352.1[/C][C]2.53771550808991[/C][C]6[/C][/ROW]
[ROW][C]3[/C][C]365.075[/C][C]3.7562170686299[/C][C]8.89999999999998[/C][/ROW]
[ROW][C]4[/C][C]373.4[/C][C]3.88243909589491[/C][C]8.5[/C][/ROW]
[ROW][C]5[/C][C]386.025[/C][C]4.59664732894167[/C][C]10.4[/C][/ROW]
[ROW][C]6[/C][C]401.15[/C][C]4.85832618638698[/C][C]11.2[/C][/ROW]
[ROW][C]7[/C][C]416.1[/C][C]5.04116388677588[/C][C]11.2[/C][/ROW]
[ROW][C]8[/C][C]426.8[/C][C]3.42928563989645[/C][C]8.19999999999999[/C][/ROW]
[ROW][C]9[/C][C]438.95[/C][C]3.92640632979657[/C][C]9.19999999999999[/C][/ROW]
[ROW][C]10[/C][C]449.075[/C][C]3.79418414594407[/C][C]8[/C][/ROW]
[ROW][C]11[/C][C]462.425[/C][C]3.40036762718386[/C][C]7.80000000000001[/C][/ROW]
[ROW][C]12[/C][C]473.225[/C][C]3.81171439993432[/C][C]8.80000000000001[/C][/ROW]
[ROW][C]13[/C][C]484.25[/C][C]3.66651514838454[/C][C]8.5[/C][/ROW]
[ROW][C]14[/C][C]496.95[/C][C]4.39279713470433[/C][C]10.2[/C][/ROW]
[ROW][C]15[/C][C]511.875[/C][C]7.77833529747849[/C][C]18.3[/C][/ROW]
[ROW][C]16[/C][C]532.075[/C][C]5.72501819502201[/C][C]13.3[/C][/ROW]
[ROW][C]17[/C][C]549.9[/C][C]4.52769256906871[/C][C]10.5[/C][/ROW]
[ROW][C]18[/C][C]562.7[/C][C]3.85140666943044[/C][C]8.89999999999998[/C][/ROW]
[ROW][C]19[/C][C]571.675[/C][C]2.49582985531198[/C][C]5.89999999999998[/C][/ROW]
[ROW][C]20[/C][C]581.95[/C][C]3.9644251369734[/C][C]9.39999999999998[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283481&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283481&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	344.1	2.65832027165025	6.19999999999999
2	352.1	2.53771550808991	6
3	365.075	3.7562170686299	8.89999999999998
4	373.4	3.88243909589491	8.5
5	386.025	4.59664732894167	10.4
6	401.15	4.85832618638698	11.2
7	416.1	5.04116388677588	11.2
8	426.8	3.42928563989645	8.19999999999999
9	438.95	3.92640632979657	9.19999999999999
10	449.075	3.79418414594407	8
11	462.425	3.40036762718386	7.80000000000001
12	473.225	3.81171439993432	8.80000000000001
13	484.25	3.66651514838454	8.5
14	496.95	4.39279713470433	10.2
15	511.875	7.77833529747849	18.3
16	532.075	5.72501819502201	13.3
17	549.9	4.52769256906871	10.5
18	562.7	3.85140666943044	8.89999999999998
19	571.675	2.49582985531198	5.89999999999998
20	581.95	3.9644251369734	9.39999999999998

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	2.37950152626982
beta	0.00375877219221578
S.D.	0.00357064050678111
T-STAT	1.05268849806565
p-value	0.306410926910793

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 2.37950152626982 \tabularnewline
beta & 0.00375877219221578 \tabularnewline
S.D. & 0.00357064050678111 \tabularnewline
T-STAT & 1.05268849806565 \tabularnewline
p-value & 0.306410926910793 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283481&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.37950152626982[/C][/ROW]
[ROW][C]beta[/C][C]0.00375877219221578[/C][/ROW]
[ROW][C]S.D.[/C][C]0.00357064050678111[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.05268849806565[/C][/ROW]
[ROW][C]p-value[/C][C]0.306410926910793[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283481&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283481&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	2.37950152626982
beta	0.00375877219221578
S.D.	0.00357064050678111
T-STAT	1.05268849806565
p-value	0.306410926910793

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.27678384099907
beta	0.433873426788339
S.D.	0.363793361137073
T-STAT	1.19263701083556
p-value	0.248496795162383
Lambda	0.566126573211661

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.27678384099907 \tabularnewline
beta & 0.433873426788339 \tabularnewline
S.D. & 0.363793361137073 \tabularnewline
T-STAT & 1.19263701083556 \tabularnewline
p-value & 0.248496795162383 \tabularnewline
Lambda & 0.566126573211661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283481&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.27678384099907[/C][/ROW]
[ROW][C]beta[/C][C]0.433873426788339[/C][/ROW]
[ROW][C]S.D.[/C][C]0.363793361137073[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.19263701083556[/C][/ROW]
[ROW][C]p-value[/C][C]0.248496795162383[/C][/ROW]
[ROW][C]Lambda[/C][C]0.566126573211661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283481&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283481&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	-1.27678384099907
beta	0.433873426788339
S.D.	0.363793361137073
T-STAT	1.19263701083556
p-value	0.248496795162383
Lambda	0.566126573211661

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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')

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code