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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

Tue, 20 Dec 2016 11:30:19 +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/20/t1482230026w3ccd62ixt9j1zn.htm/, Retrieved Sun, 28 Apr 2024 10:58:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301584, Retrieved Sun, 28 Apr 2024 10:58:39 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

116

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

-       [Standard Deviation-Mean Plot] [Standard Deviatio...] [2016-12-20 10:30:19] [86c9a777e8dbb7ef3face68c75fc8376] [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=301584&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=301584&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301584&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	2064	2005.44640235716	5652
2	7323.5	1361.46875903128	3666
3	12102.5	3268.87682962707	9432
4	14438	3231.62587843671	9366
5	7680	795.899491141941	2574
6	11507	3799.22886912594	15666
7	18864.5	4615.39070541556	17400
8	10521	4001.29419972179	13590
9	7748	4468.91030036711	16722
10	12245.5	4679.84367454532	14922

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2064 & 2005.44640235716 & 5652 \tabularnewline
2 & 7323.5 & 1361.46875903128 & 3666 \tabularnewline
3 & 12102.5 & 3268.87682962707 & 9432 \tabularnewline
4 & 14438 & 3231.62587843671 & 9366 \tabularnewline
5 & 7680 & 795.899491141941 & 2574 \tabularnewline
6 & 11507 & 3799.22886912594 & 15666 \tabularnewline
7 & 18864.5 & 4615.39070541556 & 17400 \tabularnewline
8 & 10521 & 4001.29419972179 & 13590 \tabularnewline
9 & 7748 & 4468.91030036711 & 16722 \tabularnewline
10 & 12245.5 & 4679.84367454532 & 14922 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301584&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]2064[/C][C]2005.44640235716[/C][C]5652[/C][/ROW]
[ROW][C]2[/C][C]7323.5[/C][C]1361.46875903128[/C][C]3666[/C][/ROW]
[ROW][C]3[/C][C]12102.5[/C][C]3268.87682962707[/C][C]9432[/C][/ROW]
[ROW][C]4[/C][C]14438[/C][C]3231.62587843671[/C][C]9366[/C][/ROW]
[ROW][C]5[/C][C]7680[/C][C]795.899491141941[/C][C]2574[/C][/ROW]
[ROW][C]6[/C][C]11507[/C][C]3799.22886912594[/C][C]15666[/C][/ROW]
[ROW][C]7[/C][C]18864.5[/C][C]4615.39070541556[/C][C]17400[/C][/ROW]
[ROW][C]8[/C][C]10521[/C][C]4001.29419972179[/C][C]13590[/C][/ROW]
[ROW][C]9[/C][C]7748[/C][C]4468.91030036711[/C][C]16722[/C][/ROW]
[ROW][C]10[/C][C]12245.5[/C][C]4679.84367454532[/C][C]14922[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301584&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301584&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	2064	2005.44640235716	5652
2	7323.5	1361.46875903128	3666
3	12102.5	3268.87682962707	9432
4	14438	3231.62587843671	9366
5	7680	795.899491141941	2574
6	11507	3799.22886912594	15666
7	18864.5	4615.39070541556	17400
8	10521	4001.29419972179	13590
9	7748	4468.91030036711	16722
10	12245.5	4679.84367454532	14922

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	1314.28921263077
beta	0.182642955418131
S.D.	0.0856821072535963
T-STAT	2.13163472832847
p-value	0.0656257215701723

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 1314.28921263077 \tabularnewline
beta & 0.182642955418131 \tabularnewline
S.D. & 0.0856821072535963 \tabularnewline
T-STAT & 2.13163472832847 \tabularnewline
p-value & 0.0656257215701723 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301584&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]1314.28921263077[/C][/ROW]
[ROW][C]beta[/C][C]0.182642955418131[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0856821072535963[/C][/ROW]
[ROW][C]T-STAT[/C][C]2.13163472832847[/C][/ROW]
[ROW][C]p-value[/C][C]0.0656257215701723[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301584&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301584&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	1314.28921263077
beta	0.182642955418131
S.D.	0.0856821072535963
T-STAT	2.13163472832847
p-value	0.0656257215701723

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	3.68233551763869
beta	0.467554245785758
S.D.	0.307486055324651
T-STAT	1.52057056796316
p-value	0.16685797510127
Lambda	0.532445754214242

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 3.68233551763869 \tabularnewline
beta & 0.467554245785758 \tabularnewline
S.D. & 0.307486055324651 \tabularnewline
T-STAT & 1.52057056796316 \tabularnewline
p-value & 0.16685797510127 \tabularnewline
Lambda & 0.532445754214242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301584&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]3.68233551763869[/C][/ROW]
[ROW][C]beta[/C][C]0.467554245785758[/C][/ROW]
[ROW][C]S.D.[/C][C]0.307486055324651[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.52057056796316[/C][/ROW]
[ROW][C]p-value[/C][C]0.16685797510127[/C][/ROW]
[ROW][C]Lambda[/C][C]0.532445754214242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301584&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301584&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	3.68233551763869
beta	0.467554245785758
S.D.	0.307486055324651
T-STAT	1.52057056796316
p-value	0.16685797510127
Lambda	0.532445754214242

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