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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, 09 May 2011 18:13:22 +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/2011/May/09/t1304964585qim5874hey9vrv9.htm/, Retrieved Tue, 14 May 2024 15:26:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=121320, Retrieved Tue, 14 May 2024 15:26:01 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W83

Estimated Impact

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

-       [Standard Deviation-Mean Plot] [] [2011-05-09 18:13:22] [cbd72b4390db0347015264c7aa42331b] [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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121320&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' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121320&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121320&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' @ 193.190.124.24

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	30862.5	110.037872268294	235
2	31056.25	216.38603620998	515
3	32243.75	584.399620693466	1240
4	32206.25	281.613653788306	680
5	31978.75	203.034274610635	465
6	32935	496.202243713858	1060
7	33937.5	201.845650601311	475
8	34003.75	273.019382706308	605
9	33666.25	121.200591307688	265
10	33626.25	320.660126405929	715
11	33925	37.1931893407023	85
12	34055	335.236235113887	755
13	33822.5	328.367172537085	760
14	34045	312.036322672003	730
15	33106.25	433.423868747442	905
16	32306.25	432.865933825551	875
17	31121.25	542.008225644839	1130
18	31213.75	169.183086231061	340

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 30862.5 & 110.037872268294 & 235 \tabularnewline
2 & 31056.25 & 216.38603620998 & 515 \tabularnewline
3 & 32243.75 & 584.399620693466 & 1240 \tabularnewline
4 & 32206.25 & 281.613653788306 & 680 \tabularnewline
5 & 31978.75 & 203.034274610635 & 465 \tabularnewline
6 & 32935 & 496.202243713858 & 1060 \tabularnewline
7 & 33937.5 & 201.845650601311 & 475 \tabularnewline
8 & 34003.75 & 273.019382706308 & 605 \tabularnewline
9 & 33666.25 & 121.200591307688 & 265 \tabularnewline
10 & 33626.25 & 320.660126405929 & 715 \tabularnewline
11 & 33925 & 37.1931893407023 & 85 \tabularnewline
12 & 34055 & 335.236235113887 & 755 \tabularnewline
13 & 33822.5 & 328.367172537085 & 760 \tabularnewline
14 & 34045 & 312.036322672003 & 730 \tabularnewline
15 & 33106.25 & 433.423868747442 & 905 \tabularnewline
16 & 32306.25 & 432.865933825551 & 875 \tabularnewline
17 & 31121.25 & 542.008225644839 & 1130 \tabularnewline
18 & 31213.75 & 169.183086231061 & 340 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121320&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]30862.5[/C][C]110.037872268294[/C][C]235[/C][/ROW]
[ROW][C]2[/C][C]31056.25[/C][C]216.38603620998[/C][C]515[/C][/ROW]
[ROW][C]3[/C][C]32243.75[/C][C]584.399620693466[/C][C]1240[/C][/ROW]
[ROW][C]4[/C][C]32206.25[/C][C]281.613653788306[/C][C]680[/C][/ROW]
[ROW][C]5[/C][C]31978.75[/C][C]203.034274610635[/C][C]465[/C][/ROW]
[ROW][C]6[/C][C]32935[/C][C]496.202243713858[/C][C]1060[/C][/ROW]
[ROW][C]7[/C][C]33937.5[/C][C]201.845650601311[/C][C]475[/C][/ROW]
[ROW][C]8[/C][C]34003.75[/C][C]273.019382706308[/C][C]605[/C][/ROW]
[ROW][C]9[/C][C]33666.25[/C][C]121.200591307688[/C][C]265[/C][/ROW]
[ROW][C]10[/C][C]33626.25[/C][C]320.660126405929[/C][C]715[/C][/ROW]
[ROW][C]11[/C][C]33925[/C][C]37.1931893407023[/C][C]85[/C][/ROW]
[ROW][C]12[/C][C]34055[/C][C]335.236235113887[/C][C]755[/C][/ROW]
[ROW][C]13[/C][C]33822.5[/C][C]328.367172537085[/C][C]760[/C][/ROW]
[ROW][C]14[/C][C]34045[/C][C]312.036322672003[/C][C]730[/C][/ROW]
[ROW][C]15[/C][C]33106.25[/C][C]433.423868747442[/C][C]905[/C][/ROW]
[ROW][C]16[/C][C]32306.25[/C][C]432.865933825551[/C][C]875[/C][/ROW]
[ROW][C]17[/C][C]31121.25[/C][C]542.008225644839[/C][C]1130[/C][/ROW]
[ROW][C]18[/C][C]31213.75[/C][C]169.183086231061[/C][C]340[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121320&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121320&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	30862.5	110.037872268294	235
2	31056.25	216.38603620998	515
3	32243.75	584.399620693466	1240
4	32206.25	281.613653788306	680
5	31978.75	203.034274610635	465
6	32935	496.202243713858	1060
7	33937.5	201.845650601311	475
8	34003.75	273.019382706308	605
9	33666.25	121.200591307688	265
10	33626.25	320.660126405929	715
11	33925	37.1931893407023	85
12	34055	335.236235113887	755
13	33822.5	328.367172537085	760
14	34045	312.036322672003	730
15	33106.25	433.423868747442	905
16	32306.25	432.865933825551	875
17	31121.25	542.008225644839	1130
18	31213.75	169.183086231061	340

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	636.070263053413
beta	-0.0102532382640444
S.D.	0.0324564902603819
T-STAT	-0.315907178557753
p-value	0.756156513140967

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 636.070263053413 \tabularnewline
beta & -0.0102532382640444 \tabularnewline
S.D. & 0.0324564902603819 \tabularnewline
T-STAT & -0.315907178557753 \tabularnewline
p-value & 0.756156513140967 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121320&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]636.070263053413[/C][/ROW]
[ROW][C]beta[/C][C]-0.0102532382640444[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0324564902603819[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.315907178557753[/C][/ROW]
[ROW][C]p-value[/C][C]0.756156513140967[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121320&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121320&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	636.070263053413
beta	-0.0102532382640444
S.D.	0.0324564902603819
T-STAT	-0.315907178557753
p-value	0.756156513140967

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	18.8826716884395
beta	-1.2837854344835
S.D.	4.67511983578548
T-STAT	-0.274599471152981
p-value	0.787137996663762
Lambda	2.2837854344835

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 18.8826716884395 \tabularnewline
beta & -1.2837854344835 \tabularnewline
S.D. & 4.67511983578548 \tabularnewline
T-STAT & -0.274599471152981 \tabularnewline
p-value & 0.787137996663762 \tabularnewline
Lambda & 2.2837854344835 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=121320&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]18.8826716884395[/C][/ROW]
[ROW][C]beta[/C][C]-1.2837854344835[/C][/ROW]
[ROW][C]S.D.[/C][C]4.67511983578548[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.274599471152981[/C][/ROW]
[ROW][C]p-value[/C][C]0.787137996663762[/C][/ROW]
[ROW][C]Lambda[/C][C]2.2837854344835[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=121320&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=121320&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	18.8826716884395
beta	-1.2837854344835
S.D.	4.67511983578548
T-STAT	-0.274599471152981
p-value	0.787137996663762
Lambda	2.2837854344835

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')

Free Statistics

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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code