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Author's title

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

Sat, 10 Dec 2016 18:40:30 +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/2016/Dec/10/t1481391654w6wlx591glqyuda.htm/, Retrieved Fri, 01 Nov 2024 03:38:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298739, Retrieved Fri, 01 Nov 2024 03:38:43 +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] [""N2582"" deel 2] [2016-12-10 17:40:30] [afe7f6443461a2cd6ee0b843643e84a9] [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=298739&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=298739&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298739&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	4224.01666666667	111.145096267188	364.2
2	4570.95	109.290542716526	355
3	4980.2	115.047784538742	346
4	5392.63333333333	165.613741927267	497.599999999999
5	5748.95	67.0652938289518	210.400000000001
6	6048.71666666667	88.9040937122014	280.2
7	6286.16666666667	115.953433704564	351.8
8	6621.28333333333	71.0003051636634	213.2
9	6835.46666666667	57.3124979759427	204.400000000001
10	6958.8	21.5957667809491	63
11	NaN	NA	-Inf
12	NaN	NA	-Inf

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 4224.01666666667 & 111.145096267188 & 364.2 \tabularnewline
2 & 4570.95 & 109.290542716526 & 355 \tabularnewline
3 & 4980.2 & 115.047784538742 & 346 \tabularnewline
4 & 5392.63333333333 & 165.613741927267 & 497.599999999999 \tabularnewline
5 & 5748.95 & 67.0652938289518 & 210.400000000001 \tabularnewline
6 & 6048.71666666667 & 88.9040937122014 & 280.2 \tabularnewline
7 & 6286.16666666667 & 115.953433704564 & 351.8 \tabularnewline
8 & 6621.28333333333 & 71.0003051636634 & 213.2 \tabularnewline
9 & 6835.46666666667 & 57.3124979759427 & 204.400000000001 \tabularnewline
10 & 6958.8 & 21.5957667809491 & 63 \tabularnewline
11 & NaN & NA & -Inf \tabularnewline
12 & NaN & NA & -Inf \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298739&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]4224.01666666667[/C][C]111.145096267188[/C][C]364.2[/C][/ROW]
[ROW][C]2[/C][C]4570.95[/C][C]109.290542716526[/C][C]355[/C][/ROW]
[ROW][C]3[/C][C]4980.2[/C][C]115.047784538742[/C][C]346[/C][/ROW]
[ROW][C]4[/C][C]5392.63333333333[/C][C]165.613741927267[/C][C]497.599999999999[/C][/ROW]
[ROW][C]5[/C][C]5748.95[/C][C]67.0652938289518[/C][C]210.400000000001[/C][/ROW]
[ROW][C]6[/C][C]6048.71666666667[/C][C]88.9040937122014[/C][C]280.2[/C][/ROW]
[ROW][C]7[/C][C]6286.16666666667[/C][C]115.953433704564[/C][C]351.8[/C][/ROW]
[ROW][C]8[/C][C]6621.28333333333[/C][C]71.0003051636634[/C][C]213.2[/C][/ROW]
[ROW][C]9[/C][C]6835.46666666667[/C][C]57.3124979759427[/C][C]204.400000000001[/C][/ROW]
[ROW][C]10[/C][C]6958.8[/C][C]21.5957667809491[/C][C]63[/C][/ROW]
[ROW][C]11[/C][C]NaN[/C][C]NA[/C][C]-Inf[/C][/ROW]
[ROW][C]12[/C][C]NaN[/C][C]NA[/C][C]-Inf[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298739&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298739&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	4224.01666666667	111.145096267188	364.2
2	4570.95	109.290542716526	355
3	4980.2	115.047784538742	346
4	5392.63333333333	165.613741927267	497.599999999999
5	5748.95	67.0652938289518	210.400000000001
6	6048.71666666667	88.9040937122014	280.2
7	6286.16666666667	115.953433704564	351.8
8	6621.28333333333	71.0003051636634	213.2
9	6835.46666666667	57.3124979759427	204.400000000001
10	6958.8	21.5957667809491	63
11	NaN	NA	-Inf
12	NaN	NA	-Inf

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	248.764226735964
beta	-0.0271335206663231
S.D.	0.0112912479660171
T-STAT	-2.40305772647859
p-value	0.0429711947399758

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 248.764226735964 \tabularnewline
beta & -0.0271335206663231 \tabularnewline
S.D. & 0.0112912479660171 \tabularnewline
T-STAT & -2.40305772647859 \tabularnewline
p-value & 0.0429711947399758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298739&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]248.764226735964[/C][/ROW]
[ROW][C]beta[/C][C]-0.0271335206663231[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0112912479660171[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.40305772647859[/C][/ROW]
[ROW][C]p-value[/C][C]0.0429711947399758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298739&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298739&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	248.764226735964
beta	-0.0271335206663231
S.D.	0.0112912479660171
T-STAT	-2.40305772647859
p-value	0.0429711947399758

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	22.3013624784228
beta	-2.06924232045858
S.D.	0.898196855884644
T-STAT	-2.3037737294466
p-value	0.0501743901265797
Lambda	3.06924232045858

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 22.3013624784228 \tabularnewline
beta & -2.06924232045858 \tabularnewline
S.D. & 0.898196855884644 \tabularnewline
T-STAT & -2.3037737294466 \tabularnewline
p-value & 0.0501743901265797 \tabularnewline
Lambda & 3.06924232045858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298739&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]22.3013624784228[/C][/ROW]
[ROW][C]beta[/C][C]-2.06924232045858[/C][/ROW]
[ROW][C]S.D.[/C][C]0.898196855884644[/C][/ROW]
[ROW][C]T-STAT[/C][C]-2.3037737294466[/C][/ROW]
[ROW][C]p-value[/C][C]0.0501743901265797[/C][/ROW]
[ROW][C]Lambda[/C][C]3.06924232045858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298739&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298739&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	22.3013624784228
beta	-2.06924232045858
S.D.	0.898196855884644
T-STAT	-2.3037737294466
p-value	0.0501743901265797
Lambda	3.06924232045858

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code