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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 13:49:55 +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/t1481374226xg8keqgx1bfxwx7.htm/, Retrieved Mon, 06 May 2024 07:08:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298670, Retrieved Mon, 06 May 2024 07:08:45 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD    [Standard Deviation-Mean Plot] [N2380 Standard de...] [2016-12-10 12:49:55] [1eb03b74c4069f30e782d39ada1a3213] [Current]

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Boxplots

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=298670&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=298670&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298670&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	6483.33333333333	76.0135554099439	275
2	6853.41666666667	181.832819486539	471
3	7132.33333333333	83.5445807320677	291
4	7027.33333333333	66.5054110352661	218
5	7150.75	49.0419579173144	202
6	7299.75	128.487795670887	348
7	7753.25	108.560100656482	329
8	7879	159.894283256725	450
9	8022.16666666667	126.973750568113	375

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 6483.33333333333 & 76.0135554099439 & 275 \tabularnewline
2 & 6853.41666666667 & 181.832819486539 & 471 \tabularnewline
3 & 7132.33333333333 & 83.5445807320677 & 291 \tabularnewline
4 & 7027.33333333333 & 66.5054110352661 & 218 \tabularnewline
5 & 7150.75 & 49.0419579173144 & 202 \tabularnewline
6 & 7299.75 & 128.487795670887 & 348 \tabularnewline
7 & 7753.25 & 108.560100656482 & 329 \tabularnewline
8 & 7879 & 159.894283256725 & 450 \tabularnewline
9 & 8022.16666666667 & 126.973750568113 & 375 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298670&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]6483.33333333333[/C][C]76.0135554099439[/C][C]275[/C][/ROW]
[ROW][C]2[/C][C]6853.41666666667[/C][C]181.832819486539[/C][C]471[/C][/ROW]
[ROW][C]3[/C][C]7132.33333333333[/C][C]83.5445807320677[/C][C]291[/C][/ROW]
[ROW][C]4[/C][C]7027.33333333333[/C][C]66.5054110352661[/C][C]218[/C][/ROW]
[ROW][C]5[/C][C]7150.75[/C][C]49.0419579173144[/C][C]202[/C][/ROW]
[ROW][C]6[/C][C]7299.75[/C][C]128.487795670887[/C][C]348[/C][/ROW]
[ROW][C]7[/C][C]7753.25[/C][C]108.560100656482[/C][C]329[/C][/ROW]
[ROW][C]8[/C][C]7879[/C][C]159.894283256725[/C][C]450[/C][/ROW]
[ROW][C]9[/C][C]8022.16666666667[/C][C]126.973750568113[/C][C]375[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298670&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298670&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	6483.33333333333	76.0135554099439	275
2	6853.41666666667	181.832819486539	471
3	7132.33333333333	83.5445807320677	291
4	7027.33333333333	66.5054110352661	218
5	7150.75	49.0419579173144	202
6	7299.75	128.487795670887	348
7	7753.25	108.560100656482	329
8	7879	159.894283256725	450
9	8022.16666666667	126.973750568113	375

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-109.302083739076
beta	0.0299471505922392
S.D.	0.031099552529658
T-STAT	0.962944742168885
p-value	0.367652309271461

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -109.302083739076 \tabularnewline
beta & 0.0299471505922392 \tabularnewline
S.D. & 0.031099552529658 \tabularnewline
T-STAT & 0.962944742168885 \tabularnewline
p-value & 0.367652309271461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298670&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-109.302083739076[/C][/ROW]
[ROW][C]beta[/C][C]0.0299471505922392[/C][/ROW]
[ROW][C]S.D.[/C][C]0.031099552529658[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.962944742168885[/C][/ROW]
[ROW][C]p-value[/C][C]0.367652309271461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298670&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298670&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	-109.302083739076
beta	0.0299471505922392
S.D.	0.031099552529658
T-STAT	0.962944742168885
p-value	0.367652309271461

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-16.6914081310191
beta	2.39583786116863
S.D.	2.15921867186297
T-STAT	1.10958556092029
p-value	0.303835784063611
Lambda	-1.39583786116863

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -16.6914081310191 \tabularnewline
beta & 2.39583786116863 \tabularnewline
S.D. & 2.15921867186297 \tabularnewline
T-STAT & 1.10958556092029 \tabularnewline
p-value & 0.303835784063611 \tabularnewline
Lambda & -1.39583786116863 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298670&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-16.6914081310191[/C][/ROW]
[ROW][C]beta[/C][C]2.39583786116863[/C][/ROW]
[ROW][C]S.D.[/C][C]2.15921867186297[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.10958556092029[/C][/ROW]
[ROW][C]p-value[/C][C]0.303835784063611[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.39583786116863[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298670&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298670&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	-16.6914081310191
beta	2.39583786116863
S.D.	2.15921867186297
T-STAT	1.10958556092029
p-value	0.303835784063611
Lambda	-1.39583786116863

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