Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_smp.wasp

Title produced by software

Standard Deviation-Mean Plot

Date of computation

Thu, 27 Dec 2012 16:24:21 -0500

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/2012/Dec/27/t1356643485oel0tsl013dbl8d.htm/, Retrieved Tue, 16 Apr 2024 12:50:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=204796, Retrieved Tue, 16 Apr 2024 12:50:48 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

148

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

-     [(Partial) Autocorrelation Function] [Autocorrelatie In...] [2012-11-12 10:59:56] [41982c7b3984978a38ca838fef047984]
- RMPD  [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:12:14] [41982c7b3984978a38ca838fef047984]
- R P     [Bootstrap Plot - Central Tendency] [Bootstrap Plot (m...] [2012-12-27 20:14:03] [41982c7b3984978a38ca838fef047984]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:38:33] [41982c7b3984978a38ca838fef047984]
- R  D        [Blocked Bootstrap Plot - Central Tendency] [Bootstrap Plot (g...] [2012-12-27 20:42:04] [41982c7b3984978a38ca838fef047984]
- RM              [Standard Deviation-Mean Plot] [Spreidings- en ge...] [2012-12-27 21:24:21] [97ff841fcf87514e420f2e9629cfd808] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

0.75
0.75
0.77
0.78
0.79
1.01
1.16
1.14
1.12
1.1
1.1
1.1
1.1
1.09
1.09
1.1
1.1
1.17
1.15
1.04
0.94
0.88
0.85
0.85
0.85
0.84
0.83
0.8
0.78
1.02
1.19
1.1
0.96
0.87
0.83
0.82
0.81
0.78
0.79
0.8
0.79
0.97
1.01
0.92
0.87
0.84
0.81
0.81
0.83
0.83
0.85
0.88
0.89
1.21
1.32
1.33
1.23
1.16
1.12
1.06
1.08
1.09
1.03
1.04
1.05
1.19
1.14
1.05
0.95
0.87
0.86
0.85

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	'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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	'Gertrude Mary Cox' @ cox.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	0.964166666666667	0.177018660204528	0.41
2	1.03	0.117318525236368	0.32
3	0.9075	0.131088103613909	0.41
4	0.85	0.0767522578880197	0.23
5	1.05916666666667	0.194630574694883	0.5
6	1.01666666666667	0.111137370634342	0.34

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 0.964166666666667 & 0.177018660204528 & 0.41 \tabularnewline
2 & 1.03 & 0.117318525236368 & 0.32 \tabularnewline
3 & 0.9075 & 0.131088103613909 & 0.41 \tabularnewline
4 & 0.85 & 0.0767522578880197 & 0.23 \tabularnewline
5 & 1.05916666666667 & 0.194630574694883 & 0.5 \tabularnewline
6 & 1.01666666666667 & 0.111137370634342 & 0.34 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&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]0.964166666666667[/C][C]0.177018660204528[/C][C]0.41[/C][/ROW]
[ROW][C]2[/C][C]1.03[/C][C]0.117318525236368[/C][C]0.32[/C][/ROW]
[ROW][C]3[/C][C]0.9075[/C][C]0.131088103613909[/C][C]0.41[/C][/ROW]
[ROW][C]4[/C][C]0.85[/C][C]0.0767522578880197[/C][C]0.23[/C][/ROW]
[ROW][C]5[/C][C]1.05916666666667[/C][C]0.194630574694883[/C][C]0.5[/C][/ROW]
[ROW][C]6[/C][C]1.01666666666667[/C][C]0.111137370634342[/C][C]0.34[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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	0.964166666666667	0.177018660204528	0.41
2	1.03	0.117318525236368	0.32
3	0.9075	0.131088103613909	0.41
4	0.85	0.0767522578880197	0.23
5	1.05916666666667	0.194630574694883	0.5
6	1.01666666666667	0.111137370634342	0.34

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-0.172363484454058
beta	0.316109206176988
S.D.	0.223526970359861
T-STAT	1.41418821034471
p-value	0.230206541131741

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -0.172363484454058 \tabularnewline
beta & 0.316109206176988 \tabularnewline
S.D. & 0.223526970359861 \tabularnewline
T-STAT & 1.41418821034471 \tabularnewline
p-value & 0.230206541131741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-0.172363484454058[/C][/ROW]
[ROW][C]beta[/C][C]0.316109206176988[/C][/ROW]
[ROW][C]S.D.[/C][C]0.223526970359861[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.41418821034471[/C][/ROW]
[ROW][C]p-value[/C][C]0.230206541131741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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	-0.172363484454058
beta	0.316109206176988
S.D.	0.223526970359861
T-STAT	1.41418821034471
p-value	0.230206541131741

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-1.97057982871513
beta	2.51209923186973
S.D.	1.56378956530374
T-STAT	1.60641769686051
p-value	0.183457168577422
Lambda	-1.51209923186973

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -1.97057982871513 \tabularnewline
beta & 2.51209923186973 \tabularnewline
S.D. & 1.56378956530374 \tabularnewline
T-STAT & 1.60641769686051 \tabularnewline
p-value & 0.183457168577422 \tabularnewline
Lambda & -1.51209923186973 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=204796&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-1.97057982871513[/C][/ROW]
[ROW][C]beta[/C][C]2.51209923186973[/C][/ROW]
[ROW][C]S.D.[/C][C]1.56378956530374[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.60641769686051[/C][/ROW]
[ROW][C]p-value[/C][C]0.183457168577422[/C][/ROW]
[ROW][C]Lambda[/C][C]-1.51209923186973[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=204796&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=204796&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	-1.97057982871513
beta	2.51209923186973
S.D.	1.56378956530374
T-STAT	1.60641769686051
p-value	0.183457168577422
Lambda	-1.51209923186973

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 50 ; par2 = 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