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

Tue, 18 Nov 2014 23:13:13 +0000

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/2014/Nov/18/t1416352430ruwo8921vyf4fnj.htm/, Retrieved Tue, 28 May 2024 17:35:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=256291, Retrieved Tue, 28 May 2024 17:35:22 +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

132

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

-       [Standard Deviation-Mean Plot] [Asielverzoeken - ...] [2014-11-18 23:13:13] [db747b603bff859876183158e28e8010] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

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	'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=256291&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=256291&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256291&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	1272.91666666667	220.38662652601	625
2	1346.66666666667	154.409922745995	545
3	1262.91666666667	246.774265025322	745
4	1219.58333333333	93.8678552137218	285
5	1097.5	163.755638348452	485
6	1432.08333333333	229.341531081459	690

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 1272.91666666667 & 220.38662652601 & 625 \tabularnewline
2 & 1346.66666666667 & 154.409922745995 & 545 \tabularnewline
3 & 1262.91666666667 & 246.774265025322 & 745 \tabularnewline
4 & 1219.58333333333 & 93.8678552137218 & 285 \tabularnewline
5 & 1097.5 & 163.755638348452 & 485 \tabularnewline
6 & 1432.08333333333 & 229.341531081459 & 690 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256291&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]1272.91666666667[/C][C]220.38662652601[/C][C]625[/C][/ROW]
[ROW][C]2[/C][C]1346.66666666667[/C][C]154.409922745995[/C][C]545[/C][/ROW]
[ROW][C]3[/C][C]1262.91666666667[/C][C]246.774265025322[/C][C]745[/C][/ROW]
[ROW][C]4[/C][C]1219.58333333333[/C][C]93.8678552137218[/C][C]285[/C][/ROW]
[ROW][C]5[/C][C]1097.5[/C][C]163.755638348452[/C][C]485[/C][/ROW]
[ROW][C]6[/C][C]1432.08333333333[/C][C]229.341531081459[/C][C]690[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256291&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256291&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	1272.91666666667	220.38662652601	625
2	1346.66666666667	154.409922745995	545
3	1262.91666666667	246.774265025322	745
4	1219.58333333333	93.8678552137218	285
5	1097.5	163.755638348452	485
6	1432.08333333333	229.341531081459	690

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	-67.1264494556192
beta	0.198029421577813
S.D.	0.23461385477574
T-STAT	0.844065333511964
p-value	0.446156239223565

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -67.1264494556192 \tabularnewline
beta & 0.198029421577813 \tabularnewline
S.D. & 0.23461385477574 \tabularnewline
T-STAT & 0.844065333511964 \tabularnewline
p-value & 0.446156239223565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256291&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-67.1264494556192[/C][/ROW]
[ROW][C]beta[/C][C]0.198029421577813[/C][/ROW]
[ROW][C]S.D.[/C][C]0.23461385477574[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.844065333511964[/C][/ROW]
[ROW][C]p-value[/C][C]0.446156239223565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256291&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256291&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	-67.1264494556192
beta	0.198029421577813
S.D.	0.23461385477574
T-STAT	0.844065333511964
p-value	0.446156239223565

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	-5.10795785159544
beta	1.43847224105275
S.D.	1.86466208086859
T-STAT	0.771438565631519
p-value	0.483489737246332
Lambda	-0.43847224105275

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -5.10795785159544 \tabularnewline
beta & 1.43847224105275 \tabularnewline
S.D. & 1.86466208086859 \tabularnewline
T-STAT & 0.771438565631519 \tabularnewline
p-value & 0.483489737246332 \tabularnewline
Lambda & -0.43847224105275 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=256291&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-5.10795785159544[/C][/ROW]
[ROW][C]beta[/C][C]1.43847224105275[/C][/ROW]
[ROW][C]S.D.[/C][C]1.86466208086859[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.771438565631519[/C][/ROW]
[ROW][C]p-value[/C][C]0.483489737246332[/C][/ROW]
[ROW][C]Lambda[/C][C]-0.43847224105275[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=256291&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=256291&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	-5.10795785159544
beta	1.43847224105275
S.D.	1.86466208086859
T-STAT	0.771438565631519
p-value	0.483489737246332
Lambda	-0.43847224105275

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