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Author

*The author of this computation has been verified*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Mon, 18 Dec 2017 12:13:08 +0100

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/2017/Dec/18/t1513596077rgji17wxvj5ptek.htm/, Retrieved Tue, 14 May 2024 11:15:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310136, Retrieved Tue, 14 May 2024 11:15:11 +0000

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No (this computation is public)

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Estimated Impact

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

-       [Standard Deviation-Mean Plot] [Datareeks 3.1 - S...] [2017-12-18 11:13:08] [228f385b091a4ec8014a0b8722ae7714] [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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310136&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310136&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	Big Analytics Cloud Computing Center

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	102.808333333333	14.9009126220409	46.3
2	103.883333333333	13.6321700622484	45.7
3	97.9666666666667	11.6911258757412	35.2
4	94.7666666666667	9.95337615935905	33.3
5	95.5666666666667	11.1351477381989	32.9
6	98.325	14.2410498208524	45.8
7	103.125	12.2270285545069	41.3
8	102.575	14.1407293755565	52.2
9	98.7333333333333	13.8121378329045	41.9
10	91.8166666666667	11.3199609165189	36.8
11	100	14.6610181960686	38.2
12	108.925	11.0587789067822	35.7
13	111.958333333333	12.1376542838866	38.2
14	102.308333333333	9.72835203584519	28.6
15	99.35	11.4461188340693	37.7
16	97.1666666666667	12.4871813060313	40.5
17	97.9083333333333	10.4960995641527	37.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 102.808333333333 & 14.9009126220409 & 46.3 \tabularnewline
2 & 103.883333333333 & 13.6321700622484 & 45.7 \tabularnewline
3 & 97.9666666666667 & 11.6911258757412 & 35.2 \tabularnewline
4 & 94.7666666666667 & 9.95337615935905 & 33.3 \tabularnewline
5 & 95.5666666666667 & 11.1351477381989 & 32.9 \tabularnewline
6 & 98.325 & 14.2410498208524 & 45.8 \tabularnewline
7 & 103.125 & 12.2270285545069 & 41.3 \tabularnewline
8 & 102.575 & 14.1407293755565 & 52.2 \tabularnewline
9 & 98.7333333333333 & 13.8121378329045 & 41.9 \tabularnewline
10 & 91.8166666666667 & 11.3199609165189 & 36.8 \tabularnewline
11 & 100 & 14.6610181960686 & 38.2 \tabularnewline
12 & 108.925 & 11.0587789067822 & 35.7 \tabularnewline
13 & 111.958333333333 & 12.1376542838866 & 38.2 \tabularnewline
14 & 102.308333333333 & 9.72835203584519 & 28.6 \tabularnewline
15 & 99.35 & 11.4461188340693 & 37.7 \tabularnewline
16 & 97.1666666666667 & 12.4871813060313 & 40.5 \tabularnewline
17 & 97.9083333333333 & 10.4960995641527 & 37.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310136&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]102.808333333333[/C][C]14.9009126220409[/C][C]46.3[/C][/ROW]
[ROW][C]2[/C][C]103.883333333333[/C][C]13.6321700622484[/C][C]45.7[/C][/ROW]
[ROW][C]3[/C][C]97.9666666666667[/C][C]11.6911258757412[/C][C]35.2[/C][/ROW]
[ROW][C]4[/C][C]94.7666666666667[/C][C]9.95337615935905[/C][C]33.3[/C][/ROW]
[ROW][C]5[/C][C]95.5666666666667[/C][C]11.1351477381989[/C][C]32.9[/C][/ROW]
[ROW][C]6[/C][C]98.325[/C][C]14.2410498208524[/C][C]45.8[/C][/ROW]
[ROW][C]7[/C][C]103.125[/C][C]12.2270285545069[/C][C]41.3[/C][/ROW]
[ROW][C]8[/C][C]102.575[/C][C]14.1407293755565[/C][C]52.2[/C][/ROW]
[ROW][C]9[/C][C]98.7333333333333[/C][C]13.8121378329045[/C][C]41.9[/C][/ROW]
[ROW][C]10[/C][C]91.8166666666667[/C][C]11.3199609165189[/C][C]36.8[/C][/ROW]
[ROW][C]11[/C][C]100[/C][C]14.6610181960686[/C][C]38.2[/C][/ROW]
[ROW][C]12[/C][C]108.925[/C][C]11.0587789067822[/C][C]35.7[/C][/ROW]
[ROW][C]13[/C][C]111.958333333333[/C][C]12.1376542838866[/C][C]38.2[/C][/ROW]
[ROW][C]14[/C][C]102.308333333333[/C][C]9.72835203584519[/C][C]28.6[/C][/ROW]
[ROW][C]15[/C][C]99.35[/C][C]11.4461188340693[/C][C]37.7[/C][/ROW]
[ROW][C]16[/C][C]97.1666666666667[/C][C]12.4871813060313[/C][C]40.5[/C][/ROW]
[ROW][C]17[/C][C]97.9083333333333[/C][C]10.4960995641527[/C][C]37.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310136&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	102.808333333333	14.9009126220409	46.3
2	103.883333333333	13.6321700622484	45.7
3	97.9666666666667	11.6911258757412	35.2
4	94.7666666666667	9.95337615935905	33.3
5	95.5666666666667	11.1351477381989	32.9
6	98.325	14.2410498208524	45.8
7	103.125	12.2270285545069	41.3
8	102.575	14.1407293755565	52.2
9	98.7333333333333	13.8121378329045	41.9
10	91.8166666666667	11.3199609165189	36.8
11	100	14.6610181960686	38.2
12	108.925	11.0587789067822	35.7
13	111.958333333333	12.1376542838866	38.2
14	102.308333333333	9.72835203584519	28.6
15	99.35	11.4461188340693	37.7
16	97.1666666666667	12.4871813060313	40.5
17	97.9083333333333	10.4960995641527	37.4

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	6.4236882157345
beta	0.058497608585649
S.D.	0.0842811898083485
T-STAT	0.694076682100357
p-value	0.498243375991576

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 6.4236882157345 \tabularnewline
beta & 0.058497608585649 \tabularnewline
S.D. & 0.0842811898083485 \tabularnewline
T-STAT & 0.694076682100357 \tabularnewline
p-value & 0.498243375991576 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310136&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]6.4236882157345[/C][/ROW]
[ROW][C]beta[/C][C]0.058497608585649[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0842811898083485[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.694076682100357[/C][/ROW]
[ROW][C]p-value[/C][C]0.498243375991576[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310136&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310136&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	6.4236882157345
beta	0.058497608585649
S.D.	0.0842811898083485
T-STAT	0.694076682100357
p-value	0.498243375991576

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.0503986932413832
beta	0.531758492520296
S.D.	0.696879094177526
T-STAT	0.763057030930007
p-value	0.457263022976083
Lambda	0.468241507479704

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.0503986932413832 \tabularnewline
beta & 0.531758492520296 \tabularnewline
S.D. & 0.696879094177526 \tabularnewline
T-STAT & 0.763057030930007 \tabularnewline
p-value & 0.457263022976083 \tabularnewline
Lambda & 0.468241507479704 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310136&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.0503986932413832[/C][/ROW]
[ROW][C]beta[/C][C]0.531758492520296[/C][/ROW]
[ROW][C]S.D.[/C][C]0.696879094177526[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.763057030930007[/C][/ROW]
[ROW][C]p-value[/C][C]0.457263022976083[/C][/ROW]
[ROW][C]Lambda[/C][C]0.468241507479704[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310136&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310136&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	0.0503986932413832
beta	0.531758492520296
S.D.	0.696879094177526
T-STAT	0.763057030930007
p-value	0.457263022976083
Lambda	0.468241507479704

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code