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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

Fri, 16 May 2008 09:36:11 -0600

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/2008/May/16/t12109522038hexsfaz6zgdy4d.htm/, Retrieved Sun, 19 May 2024 18:49:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12610, Retrieved Sun, 19 May 2024 18:49:38 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

231

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

-       [Standard Deviation-Mean Plot] [] [2008-05-16 15:36:11] [0344071b671470f3024f96efc0c7614f] [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	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12610&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12610&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12610&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	'George Udny Yule' @ 72.249.76.132

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	12.295	0.0660807586719963	0.139999999999999
2	12.4025	0.0149999999999997	0.0299999999999994
3	12.4475	0.0150000000000007	0.0300000000000011
4	12.515	0.0591607978309959	0.119999999999999
5	12.625	0.0251661147842361	0.0600000000000005
6	12.765	0.0479583152331275	0.110000000000001
7	13.0325	0.125000000000000	0.290000000000001
8	13.18	0.00816496580927709	0.0199999999999996
9	13.2175	0.0320156211871646	0.0600000000000005
10	13.3375	0.0249999999999995	0.0499999999999989
11	13.375	0.0129099444873587	0.0300000000000011
12	13.42	0.0230940107675845	0.0399999999999991
13	13.5025	0.0613052471924984	0.140000000000001
14	13.6675	0.0149999999999997	0.0299999999999994
15	13.7825	0.00957427107756318	0.0199999999999996
16	13.905	0.0806225774829854	0.180000000000000
17	14.055	0.0369684550213649	0.08
18	14.15	0.0336650164612071	0.0700000000000003

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 12.295 & 0.0660807586719963 & 0.139999999999999 \tabularnewline
2 & 12.4025 & 0.0149999999999997 & 0.0299999999999994 \tabularnewline
3 & 12.4475 & 0.0150000000000007 & 0.0300000000000011 \tabularnewline
4 & 12.515 & 0.0591607978309959 & 0.119999999999999 \tabularnewline
5 & 12.625 & 0.0251661147842361 & 0.0600000000000005 \tabularnewline
6 & 12.765 & 0.0479583152331275 & 0.110000000000001 \tabularnewline
7 & 13.0325 & 0.125000000000000 & 0.290000000000001 \tabularnewline
8 & 13.18 & 0.00816496580927709 & 0.0199999999999996 \tabularnewline
9 & 13.2175 & 0.0320156211871646 & 0.0600000000000005 \tabularnewline
10 & 13.3375 & 0.0249999999999995 & 0.0499999999999989 \tabularnewline
11 & 13.375 & 0.0129099444873587 & 0.0300000000000011 \tabularnewline
12 & 13.42 & 0.0230940107675845 & 0.0399999999999991 \tabularnewline
13 & 13.5025 & 0.0613052471924984 & 0.140000000000001 \tabularnewline
14 & 13.6675 & 0.0149999999999997 & 0.0299999999999994 \tabularnewline
15 & 13.7825 & 0.00957427107756318 & 0.0199999999999996 \tabularnewline
16 & 13.905 & 0.0806225774829854 & 0.180000000000000 \tabularnewline
17 & 14.055 & 0.0369684550213649 & 0.08 \tabularnewline
18 & 14.15 & 0.0336650164612071 & 0.0700000000000003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12610&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]12.295[/C][C]0.0660807586719963[/C][C]0.139999999999999[/C][/ROW]
[ROW][C]2[/C][C]12.4025[/C][C]0.0149999999999997[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]3[/C][C]12.4475[/C][C]0.0150000000000007[/C][C]0.0300000000000011[/C][/ROW]
[ROW][C]4[/C][C]12.515[/C][C]0.0591607978309959[/C][C]0.119999999999999[/C][/ROW]
[ROW][C]5[/C][C]12.625[/C][C]0.0251661147842361[/C][C]0.0600000000000005[/C][/ROW]
[ROW][C]6[/C][C]12.765[/C][C]0.0479583152331275[/C][C]0.110000000000001[/C][/ROW]
[ROW][C]7[/C][C]13.0325[/C][C]0.125000000000000[/C][C]0.290000000000001[/C][/ROW]
[ROW][C]8[/C][C]13.18[/C][C]0.00816496580927709[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]9[/C][C]13.2175[/C][C]0.0320156211871646[/C][C]0.0600000000000005[/C][/ROW]
[ROW][C]10[/C][C]13.3375[/C][C]0.0249999999999995[/C][C]0.0499999999999989[/C][/ROW]
[ROW][C]11[/C][C]13.375[/C][C]0.0129099444873587[/C][C]0.0300000000000011[/C][/ROW]
[ROW][C]12[/C][C]13.42[/C][C]0.0230940107675845[/C][C]0.0399999999999991[/C][/ROW]
[ROW][C]13[/C][C]13.5025[/C][C]0.0613052471924984[/C][C]0.140000000000001[/C][/ROW]
[ROW][C]14[/C][C]13.6675[/C][C]0.0149999999999997[/C][C]0.0299999999999994[/C][/ROW]
[ROW][C]15[/C][C]13.7825[/C][C]0.00957427107756318[/C][C]0.0199999999999996[/C][/ROW]
[ROW][C]16[/C][C]13.905[/C][C]0.0806225774829854[/C][C]0.180000000000000[/C][/ROW]
[ROW][C]17[/C][C]14.055[/C][C]0.0369684550213649[/C][C]0.08[/C][/ROW]
[ROW][C]18[/C][C]14.15[/C][C]0.0336650164612071[/C][C]0.0700000000000003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12610&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12610&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	12.295	0.0660807586719963	0.139999999999999
2	12.4025	0.0149999999999997	0.0299999999999994
3	12.4475	0.0150000000000007	0.0300000000000011
4	12.515	0.0591607978309959	0.119999999999999
5	12.625	0.0251661147842361	0.0600000000000005
6	12.765	0.0479583152331275	0.110000000000001
7	13.0325	0.125000000000000	0.290000000000001
8	13.18	0.00816496580927709	0.0199999999999996
9	13.2175	0.0320156211871646	0.0600000000000005
10	13.3375	0.0249999999999995	0.0499999999999989
11	13.375	0.0129099444873587	0.0300000000000011
12	13.42	0.0230940107675845	0.0399999999999991
13	13.5025	0.0613052471924984	0.140000000000001
14	13.6675	0.0149999999999997	0.0299999999999994
15	13.7825	0.00957427107756318	0.0199999999999996
16	13.905	0.0806225774829854	0.180000000000000
17	14.055	0.0369684550213649	0.08
18	14.15	0.0336650164612071	0.0700000000000003

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	0.0830445101734587
beta	-0.00337904738451624
S.D.	0.0128861603673793
T-STAT	-0.262222980948625
p-value	0.796495687396567

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 0.0830445101734587 \tabularnewline
beta & -0.00337904738451624 \tabularnewline
S.D. & 0.0128861603673793 \tabularnewline
T-STAT & -0.262222980948625 \tabularnewline
p-value & 0.796495687396567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12610&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0830445101734587[/C][/ROW]
[ROW][C]beta[/C][C]-0.00337904738451624[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0128861603673793[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.262222980948625[/C][/ROW]
[ROW][C]p-value[/C][C]0.796495687396567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12610&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12610&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	0.0830445101734587
beta	-0.00337904738451624
S.D.	0.0128861603673793
T-STAT	-0.262222980948625
p-value	0.796495687396567

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-0.903431159954354
beta	-1.02050432900966
S.D.	4.30734746305744
T-STAT	-0.236921757012212
p-value	0.815724215256415
Lambda	2.02050432900966

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -0.903431159954354 \tabularnewline
beta & -1.02050432900966 \tabularnewline
S.D. & 4.30734746305744 \tabularnewline
T-STAT & -0.236921757012212 \tabularnewline
p-value & 0.815724215256415 \tabularnewline
Lambda & 2.02050432900966 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12610&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.903431159954354[/C][/ROW]
[ROW][C]beta[/C][C]-1.02050432900966[/C][/ROW]
[ROW][C]S.D.[/C][C]4.30734746305744[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.236921757012212[/C][/ROW]
[ROW][C]p-value[/C][C]0.815724215256415[/C][/ROW]
[ROW][C]Lambda[/C][C]2.02050432900966[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12610&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12610&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	-0.903431159954354
beta	-1.02050432900966
S.D.	4.30734746305744
T-STAT	-0.236921757012212
p-value	0.815724215256415
Lambda	2.02050432900966

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