Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Fri, 20 May 2011 00:03:30 +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/20/t1305849606ygptyqccbk66w0d.htm/, Retrieved Sun, 12 May 2024 15:02:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=122321, Retrieved Sun, 12 May 2024 15:02:32 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

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] [Pieter De Bock 8.3] [2011-05-20 00:03:30] [cbef39b832afec63e267b10f62c5e5c1] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

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' @ 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=122321&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=122321&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122321&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	194.73425	3.22582169118713	7.50500000000002
2	186.90275	2.92987990368206	6.696
3	176.38925	4.96274503173395	12.017
4	155.31175	21.6934696683126	46.174
5	99.83175	19.9870526820906	43.18
6	158.8605	5.37884358699278	11.478
7	149.907	4.3386401095274	9.17599999999999
8	147.31375	2.14217792211571	4.72899999999998
9	134.1545	7.33344218858603	17.52
10	126.849	2.21800811540445	4.63800000000001
11	108.7885	9.31329721419863	22.248
12	135.7575	11.7529744745745	22.656
13	144.5935	2.58221526342532	5.68600000000001
14	147.3975	1.26988332797414	2.65600000000001
15	154.73125	4.55690972589978	10.481
16	156.579	1.96559914529896	3.92400000000001
17	152.9405	6.15832534054511	14.472
18	140.57475	0.99527998573265	2.13799999999998
19	126.5725	6.70693976415474	15.164
20	121.909	1.32645417058663	3.18600000000001
21	121.8495	3.63004651026218	7.432
22	116.198	1.47733070096035	3.16499999999999
23	122.07	2.97832480879213	6.64800000000001
24	118.39925	4.55076926647206	9.956
25	114.70575	1.05104658158746	2.39500000000001

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 194.73425 & 3.22582169118713 & 7.50500000000002 \tabularnewline
2 & 186.90275 & 2.92987990368206 & 6.696 \tabularnewline
3 & 176.38925 & 4.96274503173395 & 12.017 \tabularnewline
4 & 155.31175 & 21.6934696683126 & 46.174 \tabularnewline
5 & 99.83175 & 19.9870526820906 & 43.18 \tabularnewline
6 & 158.8605 & 5.37884358699278 & 11.478 \tabularnewline
7 & 149.907 & 4.3386401095274 & 9.17599999999999 \tabularnewline
8 & 147.31375 & 2.14217792211571 & 4.72899999999998 \tabularnewline
9 & 134.1545 & 7.33344218858603 & 17.52 \tabularnewline
10 & 126.849 & 2.21800811540445 & 4.63800000000001 \tabularnewline
11 & 108.7885 & 9.31329721419863 & 22.248 \tabularnewline
12 & 135.7575 & 11.7529744745745 & 22.656 \tabularnewline
13 & 144.5935 & 2.58221526342532 & 5.68600000000001 \tabularnewline
14 & 147.3975 & 1.26988332797414 & 2.65600000000001 \tabularnewline
15 & 154.73125 & 4.55690972589978 & 10.481 \tabularnewline
16 & 156.579 & 1.96559914529896 & 3.92400000000001 \tabularnewline
17 & 152.9405 & 6.15832534054511 & 14.472 \tabularnewline
18 & 140.57475 & 0.99527998573265 & 2.13799999999998 \tabularnewline
19 & 126.5725 & 6.70693976415474 & 15.164 \tabularnewline
20 & 121.909 & 1.32645417058663 & 3.18600000000001 \tabularnewline
21 & 121.8495 & 3.63004651026218 & 7.432 \tabularnewline
22 & 116.198 & 1.47733070096035 & 3.16499999999999 \tabularnewline
23 & 122.07 & 2.97832480879213 & 6.64800000000001 \tabularnewline
24 & 118.39925 & 4.55076926647206 & 9.956 \tabularnewline
25 & 114.70575 & 1.05104658158746 & 2.39500000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122321&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]194.73425[/C][C]3.22582169118713[/C][C]7.50500000000002[/C][/ROW]
[ROW][C]2[/C][C]186.90275[/C][C]2.92987990368206[/C][C]6.696[/C][/ROW]
[ROW][C]3[/C][C]176.38925[/C][C]4.96274503173395[/C][C]12.017[/C][/ROW]
[ROW][C]4[/C][C]155.31175[/C][C]21.6934696683126[/C][C]46.174[/C][/ROW]
[ROW][C]5[/C][C]99.83175[/C][C]19.9870526820906[/C][C]43.18[/C][/ROW]
[ROW][C]6[/C][C]158.8605[/C][C]5.37884358699278[/C][C]11.478[/C][/ROW]
[ROW][C]7[/C][C]149.907[/C][C]4.3386401095274[/C][C]9.17599999999999[/C][/ROW]
[ROW][C]8[/C][C]147.31375[/C][C]2.14217792211571[/C][C]4.72899999999998[/C][/ROW]
[ROW][C]9[/C][C]134.1545[/C][C]7.33344218858603[/C][C]17.52[/C][/ROW]
[ROW][C]10[/C][C]126.849[/C][C]2.21800811540445[/C][C]4.63800000000001[/C][/ROW]
[ROW][C]11[/C][C]108.7885[/C][C]9.31329721419863[/C][C]22.248[/C][/ROW]
[ROW][C]12[/C][C]135.7575[/C][C]11.7529744745745[/C][C]22.656[/C][/ROW]
[ROW][C]13[/C][C]144.5935[/C][C]2.58221526342532[/C][C]5.68600000000001[/C][/ROW]
[ROW][C]14[/C][C]147.3975[/C][C]1.26988332797414[/C][C]2.65600000000001[/C][/ROW]
[ROW][C]15[/C][C]154.73125[/C][C]4.55690972589978[/C][C]10.481[/C][/ROW]
[ROW][C]16[/C][C]156.579[/C][C]1.96559914529896[/C][C]3.92400000000001[/C][/ROW]
[ROW][C]17[/C][C]152.9405[/C][C]6.15832534054511[/C][C]14.472[/C][/ROW]
[ROW][C]18[/C][C]140.57475[/C][C]0.99527998573265[/C][C]2.13799999999998[/C][/ROW]
[ROW][C]19[/C][C]126.5725[/C][C]6.70693976415474[/C][C]15.164[/C][/ROW]
[ROW][C]20[/C][C]121.909[/C][C]1.32645417058663[/C][C]3.18600000000001[/C][/ROW]
[ROW][C]21[/C][C]121.8495[/C][C]3.63004651026218[/C][C]7.432[/C][/ROW]
[ROW][C]22[/C][C]116.198[/C][C]1.47733070096035[/C][C]3.16499999999999[/C][/ROW]
[ROW][C]23[/C][C]122.07[/C][C]2.97832480879213[/C][C]6.64800000000001[/C][/ROW]
[ROW][C]24[/C][C]118.39925[/C][C]4.55076926647206[/C][C]9.956[/C][/ROW]
[ROW][C]25[/C][C]114.70575[/C][C]1.05104658158746[/C][C]2.39500000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122321&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122321&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	194.73425	3.22582169118713	7.50500000000002
2	186.90275	2.92987990368206	6.696
3	176.38925	4.96274503173395	12.017
4	155.31175	21.6934696683126	46.174
5	99.83175	19.9870526820906	43.18
6	158.8605	5.37884358699278	11.478
7	149.907	4.3386401095274	9.17599999999999
8	147.31375	2.14217792211571	4.72899999999998
9	134.1545	7.33344218858603	17.52
10	126.849	2.21800811540445	4.63800000000001
11	108.7885	9.31329721419863	22.248
12	135.7575	11.7529744745745	22.656
13	144.5935	2.58221526342532	5.68600000000001
14	147.3975	1.26988332797414	2.65600000000001
15	154.73125	4.55690972589978	10.481
16	156.579	1.96559914529896	3.92400000000001
17	152.9405	6.15832534054511	14.472
18	140.57475	0.99527998573265	2.13799999999998
19	126.5725	6.70693976415474	15.164
20	121.909	1.32645417058663	3.18600000000001
21	121.8495	3.63004651026218	7.432
22	116.198	1.47733070096035	3.16499999999999
23	122.07	2.97832480879213	6.64800000000001
24	118.39925	4.55076926647206	9.956
25	114.70575	1.05104658158746	2.39500000000001

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	10.4566132823898
beta	-0.0361167837722908
S.D.	0.0463112990967006
T-STAT	-0.779869804491488
p-value	0.443419359596088

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 10.4566132823898 \tabularnewline
beta & -0.0361167837722908 \tabularnewline
S.D. & 0.0463112990967006 \tabularnewline
T-STAT & -0.779869804491488 \tabularnewline
p-value & 0.443419359596088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122321&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]10.4566132823898[/C][/ROW]
[ROW][C]beta[/C][C]-0.0361167837722908[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0463112990967006[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.779869804491488[/C][/ROW]
[ROW][C]p-value[/C][C]0.443419359596088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122321&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122321&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	10.4566132823898
beta	-0.0361167837722908
S.D.	0.0463112990967006
T-STAT	-0.779869804491488
p-value	0.443419359596088

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.94137724583693
beta	-0.328497597057604
S.D.	1.05077447094554
T-STAT	-0.312624265378285
p-value	0.75738308295202
Lambda	1.3284975970576

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.94137724583693 \tabularnewline
beta & -0.328497597057604 \tabularnewline
S.D. & 1.05077447094554 \tabularnewline
T-STAT & -0.312624265378285 \tabularnewline
p-value & 0.75738308295202 \tabularnewline
Lambda & 1.3284975970576 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=122321&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.94137724583693[/C][/ROW]
[ROW][C]beta[/C][C]-0.328497597057604[/C][/ROW]
[ROW][C]S.D.[/C][C]1.05077447094554[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.312624265378285[/C][/ROW]
[ROW][C]p-value[/C][C]0.75738308295202[/C][/ROW]
[ROW][C]Lambda[/C][C]1.3284975970576[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=122321&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=122321&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	2.94137724583693
beta	-0.328497597057604
S.D.	1.05077447094554
T-STAT	-0.312624265378285
p-value	0.75738308295202
Lambda	1.3284975970576

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

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code