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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

Thu, 21 Dec 2017 13:47:00 +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/21/t1513863252ns1p4xpnuqcqaie.htm/, Retrieved Tue, 14 May 2024 09:49:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310633, Retrieved Tue, 14 May 2024 09:49:49 +0000

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

-       [Standard Deviation-Mean Plot] [] [2017-12-21 12:47:00] [6a14c6712734b6e9645e9b92d85f99d9] [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=310633&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=310633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310633&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	89.325	5.99350026733506	19
2	85.0666666666667	5.40173933828613	16
3	86.925	4.25464986274376	14.5
4	89.7583333333333	4.55580714998767	14.5
5	90.1166666666667	8.6382693272262	25.1
6	90.8583333333333	8.65767744766914	26.3
7	90.3666666666667	10.328542388875	28.6
8	92.9666666666667	8.33299393248236	24
9	90.9666666666667	9.13866245766586	28
10	97.6916666666667	9.03613536996002	27.6
11	100	9.70004686024295	31.9
12	96.0833333333333	6.89516738979797	24.1
13	88.2166666666667	12.5932762242637	39.5
14	89.575	11.4579170723288	34.1
15	77.65	11.9861662685857	37.9
16	75.6833333333333	12.6403274794555	38
17	90.4416666666667	11.8671784448716	37.4

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 89.325 & 5.99350026733506 & 19 \tabularnewline
2 & 85.0666666666667 & 5.40173933828613 & 16 \tabularnewline
3 & 86.925 & 4.25464986274376 & 14.5 \tabularnewline
4 & 89.7583333333333 & 4.55580714998767 & 14.5 \tabularnewline
5 & 90.1166666666667 & 8.6382693272262 & 25.1 \tabularnewline
6 & 90.8583333333333 & 8.65767744766914 & 26.3 \tabularnewline
7 & 90.3666666666667 & 10.328542388875 & 28.6 \tabularnewline
8 & 92.9666666666667 & 8.33299393248236 & 24 \tabularnewline
9 & 90.9666666666667 & 9.13866245766586 & 28 \tabularnewline
10 & 97.6916666666667 & 9.03613536996002 & 27.6 \tabularnewline
11 & 100 & 9.70004686024295 & 31.9 \tabularnewline
12 & 96.0833333333333 & 6.89516738979797 & 24.1 \tabularnewline
13 & 88.2166666666667 & 12.5932762242637 & 39.5 \tabularnewline
14 & 89.575 & 11.4579170723288 & 34.1 \tabularnewline
15 & 77.65 & 11.9861662685857 & 37.9 \tabularnewline
16 & 75.6833333333333 & 12.6403274794555 & 38 \tabularnewline
17 & 90.4416666666667 & 11.8671784448716 & 37.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310633&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]89.325[/C][C]5.99350026733506[/C][C]19[/C][/ROW]
[ROW][C]2[/C][C]85.0666666666667[/C][C]5.40173933828613[/C][C]16[/C][/ROW]
[ROW][C]3[/C][C]86.925[/C][C]4.25464986274376[/C][C]14.5[/C][/ROW]
[ROW][C]4[/C][C]89.7583333333333[/C][C]4.55580714998767[/C][C]14.5[/C][/ROW]
[ROW][C]5[/C][C]90.1166666666667[/C][C]8.6382693272262[/C][C]25.1[/C][/ROW]
[ROW][C]6[/C][C]90.8583333333333[/C][C]8.65767744766914[/C][C]26.3[/C][/ROW]
[ROW][C]7[/C][C]90.3666666666667[/C][C]10.328542388875[/C][C]28.6[/C][/ROW]
[ROW][C]8[/C][C]92.9666666666667[/C][C]8.33299393248236[/C][C]24[/C][/ROW]
[ROW][C]9[/C][C]90.9666666666667[/C][C]9.13866245766586[/C][C]28[/C][/ROW]
[ROW][C]10[/C][C]97.6916666666667[/C][C]9.03613536996002[/C][C]27.6[/C][/ROW]
[ROW][C]11[/C][C]100[/C][C]9.70004686024295[/C][C]31.9[/C][/ROW]
[ROW][C]12[/C][C]96.0833333333333[/C][C]6.89516738979797[/C][C]24.1[/C][/ROW]
[ROW][C]13[/C][C]88.2166666666667[/C][C]12.5932762242637[/C][C]39.5[/C][/ROW]
[ROW][C]14[/C][C]89.575[/C][C]11.4579170723288[/C][C]34.1[/C][/ROW]
[ROW][C]15[/C][C]77.65[/C][C]11.9861662685857[/C][C]37.9[/C][/ROW]
[ROW][C]16[/C][C]75.6833333333333[/C][C]12.6403274794555[/C][C]38[/C][/ROW]
[ROW][C]17[/C][C]90.4416666666667[/C][C]11.8671784448716[/C][C]37.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310633&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310633&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	89.325	5.99350026733506	19
2	85.0666666666667	5.40173933828613	16
3	86.925	4.25464986274376	14.5
4	89.7583333333333	4.55580714998767	14.5
5	90.1166666666667	8.6382693272262	25.1
6	90.8583333333333	8.65767744766914	26.3
7	90.3666666666667	10.328542388875	28.6
8	92.9666666666667	8.33299393248236	24
9	90.9666666666667	9.13866245766586	28
10	97.6916666666667	9.03613536996002	27.6
11	100	9.70004686024295	31.9
12	96.0833333333333	6.89516738979797	24.1
13	88.2166666666667	12.5932762242637	39.5
14	89.575	11.4579170723288	34.1
15	77.65	11.9861662685857	37.9
16	75.6833333333333	12.6403274794555	38
17	90.4416666666667	11.8671784448716	37.4

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	19.0426493300948
beta	-0.113194404032684
S.D.	0.112329450538758
T-STAT	-1.00770014889041
p-value	0.329578421901239

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 19.0426493300948 \tabularnewline
beta & -0.113194404032684 \tabularnewline
S.D. & 0.112329450538758 \tabularnewline
T-STAT & -1.00770014889041 \tabularnewline
p-value & 0.329578421901239 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310633&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]19.0426493300948[/C][/ROW]
[ROW][C]beta[/C][C]-0.113194404032684[/C][/ROW]
[ROW][C]S.D.[/C][C]0.112329450538758[/C][/ROW]
[ROW][C]T-STAT[/C][C]-1.00770014889041[/C][/ROW]
[ROW][C]p-value[/C][C]0.329578421901239[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310633&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310633&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	19.0426493300948
beta	-0.113194404032684
S.D.	0.112329450538758
T-STAT	-1.00770014889041
p-value	0.329578421901239

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	5.97061955482024
beta	-0.853867503127128
S.D.	1.25813512775253
T-STAT	-0.678677102556095
p-value	0.507679020382156
Lambda	1.85386750312713

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 5.97061955482024 \tabularnewline
beta & -0.853867503127128 \tabularnewline
S.D. & 1.25813512775253 \tabularnewline
T-STAT & -0.678677102556095 \tabularnewline
p-value & 0.507679020382156 \tabularnewline
Lambda & 1.85386750312713 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310633&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]5.97061955482024[/C][/ROW]
[ROW][C]beta[/C][C]-0.853867503127128[/C][/ROW]
[ROW][C]S.D.[/C][C]1.25813512775253[/C][/ROW]
[ROW][C]T-STAT[/C][C]-0.678677102556095[/C][/ROW]
[ROW][C]p-value[/C][C]0.507679020382156[/C][/ROW]
[ROW][C]Lambda[/C][C]1.85386750312713[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310633&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310633&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	5.97061955482024
beta	-0.853867503127128
S.D.	1.25813512775253
T-STAT	-0.678677102556095
p-value	0.507679020382156
Lambda	1.85386750312713

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = FALSE ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;

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