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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

Tue, 09 Aug 2011 12:09:25 -0400

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/Aug/09/t1312907280dhpfra3xh1r2vuh.htm/, Retrieved Mon, 13 May 2024 21:08:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123508, Retrieved Mon, 13 May 2024 21:08:59 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Van den Buys Daphn�

Estimated Impact

125

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

-       [Standard Deviation-Mean Plot] [Tijdreeks B-stap 21] [2011-08-09 16:09:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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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	'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123508&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123508&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	'AstonUniversity' @ aston.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	725	33.166247903554	80
2	767.5	56.7890834580027	120
3	807.5	29.8607881119482	70
4	772.5	42.7200187265877	90
5	785	65.57438524302	150
6	810	32.659863237109	80
7	837.5	41.1298755975102	100
8	755	106.614570611463	260
9	837.5	41.9324854180304	90
10	837.5	37.7491721763537	80
11	775	114.74609652039	260
12	832.5	29.8607881119482	70
13	825	63.5085296108588	130
14	832.5	153.920975395385	350
15	827.5	22.1735578260835	50
16	862.5	40.3112887414927	90
17	832.5	149.527032115713	350
18	840	40.8248290463863	80
19	895	124.498995979887	270
20	837.5	122.304265393049	280
21	895	71.8795288428261	160
22	895	127.148207485071	270
23	847.5	113.541475535007	250
24	930	91.2870929175277	190
25	897.5	124.465524008324	230
26	862.5	146.82756326158	330
27	945	75.4983443527075	180

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 725 & 33.166247903554 & 80 \tabularnewline
2 & 767.5 & 56.7890834580027 & 120 \tabularnewline
3 & 807.5 & 29.8607881119482 & 70 \tabularnewline
4 & 772.5 & 42.7200187265877 & 90 \tabularnewline
5 & 785 & 65.57438524302 & 150 \tabularnewline
6 & 810 & 32.659863237109 & 80 \tabularnewline
7 & 837.5 & 41.1298755975102 & 100 \tabularnewline
8 & 755 & 106.614570611463 & 260 \tabularnewline
9 & 837.5 & 41.9324854180304 & 90 \tabularnewline
10 & 837.5 & 37.7491721763537 & 80 \tabularnewline
11 & 775 & 114.74609652039 & 260 \tabularnewline
12 & 832.5 & 29.8607881119482 & 70 \tabularnewline
13 & 825 & 63.5085296108588 & 130 \tabularnewline
14 & 832.5 & 153.920975395385 & 350 \tabularnewline
15 & 827.5 & 22.1735578260835 & 50 \tabularnewline
16 & 862.5 & 40.3112887414927 & 90 \tabularnewline
17 & 832.5 & 149.527032115713 & 350 \tabularnewline
18 & 840 & 40.8248290463863 & 80 \tabularnewline
19 & 895 & 124.498995979887 & 270 \tabularnewline
20 & 837.5 & 122.304265393049 & 280 \tabularnewline
21 & 895 & 71.8795288428261 & 160 \tabularnewline
22 & 895 & 127.148207485071 & 270 \tabularnewline
23 & 847.5 & 113.541475535007 & 250 \tabularnewline
24 & 930 & 91.2870929175277 & 190 \tabularnewline
25 & 897.5 & 124.465524008324 & 230 \tabularnewline
26 & 862.5 & 146.82756326158 & 330 \tabularnewline
27 & 945 & 75.4983443527075 & 180 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123508&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]725[/C][C]33.166247903554[/C][C]80[/C][/ROW]
[ROW][C]2[/C][C]767.5[/C][C]56.7890834580027[/C][C]120[/C][/ROW]
[ROW][C]3[/C][C]807.5[/C][C]29.8607881119482[/C][C]70[/C][/ROW]
[ROW][C]4[/C][C]772.5[/C][C]42.7200187265877[/C][C]90[/C][/ROW]
[ROW][C]5[/C][C]785[/C][C]65.57438524302[/C][C]150[/C][/ROW]
[ROW][C]6[/C][C]810[/C][C]32.659863237109[/C][C]80[/C][/ROW]
[ROW][C]7[/C][C]837.5[/C][C]41.1298755975102[/C][C]100[/C][/ROW]
[ROW][C]8[/C][C]755[/C][C]106.614570611463[/C][C]260[/C][/ROW]
[ROW][C]9[/C][C]837.5[/C][C]41.9324854180304[/C][C]90[/C][/ROW]
[ROW][C]10[/C][C]837.5[/C][C]37.7491721763537[/C][C]80[/C][/ROW]
[ROW][C]11[/C][C]775[/C][C]114.74609652039[/C][C]260[/C][/ROW]
[ROW][C]12[/C][C]832.5[/C][C]29.8607881119482[/C][C]70[/C][/ROW]
[ROW][C]13[/C][C]825[/C][C]63.5085296108588[/C][C]130[/C][/ROW]
[ROW][C]14[/C][C]832.5[/C][C]153.920975395385[/C][C]350[/C][/ROW]
[ROW][C]15[/C][C]827.5[/C][C]22.1735578260835[/C][C]50[/C][/ROW]
[ROW][C]16[/C][C]862.5[/C][C]40.3112887414927[/C][C]90[/C][/ROW]
[ROW][C]17[/C][C]832.5[/C][C]149.527032115713[/C][C]350[/C][/ROW]
[ROW][C]18[/C][C]840[/C][C]40.8248290463863[/C][C]80[/C][/ROW]
[ROW][C]19[/C][C]895[/C][C]124.498995979887[/C][C]270[/C][/ROW]
[ROW][C]20[/C][C]837.5[/C][C]122.304265393049[/C][C]280[/C][/ROW]
[ROW][C]21[/C][C]895[/C][C]71.8795288428261[/C][C]160[/C][/ROW]
[ROW][C]22[/C][C]895[/C][C]127.148207485071[/C][C]270[/C][/ROW]
[ROW][C]23[/C][C]847.5[/C][C]113.541475535007[/C][C]250[/C][/ROW]
[ROW][C]24[/C][C]930[/C][C]91.2870929175277[/C][C]190[/C][/ROW]
[ROW][C]25[/C][C]897.5[/C][C]124.465524008324[/C][C]230[/C][/ROW]
[ROW][C]26[/C][C]862.5[/C][C]146.82756326158[/C][C]330[/C][/ROW]
[ROW][C]27[/C][C]945[/C][C]75.4983443527075[/C][C]180[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123508&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	725	33.166247903554	80
2	767.5	56.7890834580027	120
3	807.5	29.8607881119482	70
4	772.5	42.7200187265877	90
5	785	65.57438524302	150
6	810	32.659863237109	80
7	837.5	41.1298755975102	100
8	755	106.614570611463	260
9	837.5	41.9324854180304	90
10	837.5	37.7491721763537	80
11	775	114.74609652039	260
12	832.5	29.8607881119482	70
13	825	63.5085296108588	130
14	832.5	153.920975395385	350
15	827.5	22.1735578260835	50
16	862.5	40.3112887414927	90
17	832.5	149.527032115713	350
18	840	40.8248290463863	80
19	895	124.498995979887	270
20	837.5	122.304265393049	280
21	895	71.8795288428261	160
22	895	127.148207485071	270
23	847.5	113.541475535007	250
24	930	91.2870929175277	190
25	897.5	124.465524008324	230
26	862.5	146.82756326158	330
27	945	75.4983443527075	180

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-127.000389592012
beta	0.245021872365665
S.D.	0.157238409870407
T-STAT	1.55828256319564
p-value	0.131736738962461

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -127.000389592012 \tabularnewline
beta & 0.245021872365665 \tabularnewline
S.D. & 0.157238409870407 \tabularnewline
T-STAT & 1.55828256319564 \tabularnewline
p-value & 0.131736738962461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123508&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-127.000389592012[/C][/ROW]
[ROW][C]beta[/C][C]0.245021872365665[/C][/ROW]
[ROW][C]S.D.[/C][C]0.157238409870407[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.55828256319564[/C][/ROW]
[ROW][C]p-value[/C][C]0.131736738962461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123508&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123508&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	-127.000389592012
beta	0.245021872365665
S.D.	0.157238409870407
T-STAT	1.55828256319564
p-value	0.131736738962461

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-16.2447810455612
beta	3.0377173618308
S.D.	1.80787352382591
T-STAT	1.68027094915481
p-value	0.105359558003006
Lambda	-2.0377173618308

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -16.2447810455612 \tabularnewline
beta & 3.0377173618308 \tabularnewline
S.D. & 1.80787352382591 \tabularnewline
T-STAT & 1.68027094915481 \tabularnewline
p-value & 0.105359558003006 \tabularnewline
Lambda & -2.0377173618308 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123508&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-16.2447810455612[/C][/ROW]
[ROW][C]beta[/C][C]3.0377173618308[/C][/ROW]
[ROW][C]S.D.[/C][C]1.80787352382591[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.68027094915481[/C][/ROW]
[ROW][C]p-value[/C][C]0.105359558003006[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.0377173618308[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123508&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123508&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	-16.2447810455612
beta	3.0377173618308
S.D.	1.80787352382591
T-STAT	1.68027094915481
p-value	0.105359558003006
Lambda	-2.0377173618308

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