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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

Wed, 07 Dec 2016 14:29:22 +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/07/t1481120393umedgoczv2p84wo.htm/, Retrieved Tue, 07 May 2024 12:16:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298139, Retrieved Tue, 07 May 2024 12:16:45 +0000

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Original text written by user:

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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] [] [2016-12-07 13:29:22] [df90c754990be6fd2b18fcd529010a59] [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=298139&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=298139&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298139&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	2963.33333333333	572.829235752971	1780
2	3768.33333333333	607.19673812355	1840
3	4801.66666666667	478.821153427558	1480
4	5210	660	2280
5	5215	450.383674821207	1420
6	5848.33333333333	491.118081215678	1800
7	6325	695.498513167485	2820
8	6253.33333333333	969.435949718217	3220
9	5746.66666666667	1338.61076787795	4320
10	5058.33333333333	1038.0911970214	3400

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2963.33333333333 & 572.829235752971 & 1780 \tabularnewline
2 & 3768.33333333333 & 607.19673812355 & 1840 \tabularnewline
3 & 4801.66666666667 & 478.821153427558 & 1480 \tabularnewline
4 & 5210 & 660 & 2280 \tabularnewline
5 & 5215 & 450.383674821207 & 1420 \tabularnewline
6 & 5848.33333333333 & 491.118081215678 & 1800 \tabularnewline
7 & 6325 & 695.498513167485 & 2820 \tabularnewline
8 & 6253.33333333333 & 969.435949718217 & 3220 \tabularnewline
9 & 5746.66666666667 & 1338.61076787795 & 4320 \tabularnewline
10 & 5058.33333333333 & 1038.0911970214 & 3400 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298139&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]2963.33333333333[/C][C]572.829235752971[/C][C]1780[/C][/ROW]
[ROW][C]2[/C][C]3768.33333333333[/C][C]607.19673812355[/C][C]1840[/C][/ROW]
[ROW][C]3[/C][C]4801.66666666667[/C][C]478.821153427558[/C][C]1480[/C][/ROW]
[ROW][C]4[/C][C]5210[/C][C]660[/C][C]2280[/C][/ROW]
[ROW][C]5[/C][C]5215[/C][C]450.383674821207[/C][C]1420[/C][/ROW]
[ROW][C]6[/C][C]5848.33333333333[/C][C]491.118081215678[/C][C]1800[/C][/ROW]
[ROW][C]7[/C][C]6325[/C][C]695.498513167485[/C][C]2820[/C][/ROW]
[ROW][C]8[/C][C]6253.33333333333[/C][C]969.435949718217[/C][C]3220[/C][/ROW]
[ROW][C]9[/C][C]5746.66666666667[/C][C]1338.61076787795[/C][C]4320[/C][/ROW]
[ROW][C]10[/C][C]5058.33333333333[/C][C]1038.0911970214[/C][C]3400[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298139&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298139&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	2963.33333333333	572.829235752971	1780
2	3768.33333333333	607.19673812355	1840
3	4801.66666666667	478.821153427558	1480
4	5210	660	2280
5	5215	450.383674821207	1420
6	5848.33333333333	491.118081215678	1800
7	6325	695.498513167485	2820
8	6253.33333333333	969.435949718217	3220
9	5746.66666666667	1338.61076787795	4320
10	5058.33333333333	1038.0911970214	3400

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	246.119831430657
beta	0.094565090775922
S.D.	0.0906920085287086
T-STAT	1.04270588235994
p-value	0.327566820028558

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 246.119831430657 \tabularnewline
beta & 0.094565090775922 \tabularnewline
S.D. & 0.0906920085287086 \tabularnewline
T-STAT & 1.04270588235994 \tabularnewline
p-value & 0.327566820028558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298139&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]246.119831430657[/C][/ROW]
[ROW][C]beta[/C][C]0.094565090775922[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0906920085287086[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.04270588235994[/C][/ROW]
[ROW][C]p-value[/C][C]0.327566820028558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298139&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298139&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	246.119831430657
beta	0.094565090775922
S.D.	0.0906920085287086
T-STAT	1.04270588235994
p-value	0.327566820028558

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	2.33635301452932
beta	0.492305504340292
S.D.	0.515948062223352
T-STAT	0.954176477025267
p-value	0.367932458977259
Lambda	0.507694495659708

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 2.33635301452932 \tabularnewline
beta & 0.492305504340292 \tabularnewline
S.D. & 0.515948062223352 \tabularnewline
T-STAT & 0.954176477025267 \tabularnewline
p-value & 0.367932458977259 \tabularnewline
Lambda & 0.507694495659708 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298139&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]2.33635301452932[/C][/ROW]
[ROW][C]beta[/C][C]0.492305504340292[/C][/ROW]
[ROW][C]S.D.[/C][C]0.515948062223352[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.954176477025267[/C][/ROW]
[ROW][C]p-value[/C][C]0.367932458977259[/C][/ROW]
[ROW][C]Lambda[/C][C]0.507694495659708[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298139&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298139&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	2.33635301452932
beta	0.492305504340292
S.D.	0.515948062223352
T-STAT	0.954176477025267
p-value	0.367932458977259
Lambda	0.507694495659708

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