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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

Thu, 15 Dec 2011 11:08:11 -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/2011/Dec/15/t1323965312mn2w2bt85eifydz.htm/, Retrieved Wed, 08 May 2024 12:04:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=155535, Retrieved Wed, 08 May 2024 12:04:01 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

118

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

-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [WS 10 - Pearson c...] [2010-12-10 16:13:49] [033eb2749a430605d9b2be7c4aac4a0c]
-         [Kendall tau Correlation Matrix] [] [2010-12-13 18:15:16] [d7b28a0391ab3b2ddc9f9fba95a43f33]
- RMPD      [Standard Deviation-Mean Plot] [] [2010-12-24 12:03:45] [b07cd1964830aab808142229b1166ece]
-   PD          [Standard Deviation-Mean Plot] [standard dev mean...] [2011-12-15 16:08:11] [0e2c18186cab982e7ba7b89fbe242e59] [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	2 seconds
R Server	'George Udny Yule' @ yule.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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155535&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155535&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155535&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	2 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	2201.25	308.694354573346	1066
2	2466.25	322.77916036144	1117
3	2567.91666666667	302.862542578262	1142
4	2601.58333333333	258.022711591382	884
5	2588	364.745490345354	1204
6	2572.33333333333	275.379847857574	944
7	2449.91666666667	372.260284877355	1339
8	2579.33333333333	390.916018261382	1482
9	2934.25	398.295487615094	1425
10	2679.5	348.175895985714	1333

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 2201.25 & 308.694354573346 & 1066 \tabularnewline
2 & 2466.25 & 322.77916036144 & 1117 \tabularnewline
3 & 2567.91666666667 & 302.862542578262 & 1142 \tabularnewline
4 & 2601.58333333333 & 258.022711591382 & 884 \tabularnewline
5 & 2588 & 364.745490345354 & 1204 \tabularnewline
6 & 2572.33333333333 & 275.379847857574 & 944 \tabularnewline
7 & 2449.91666666667 & 372.260284877355 & 1339 \tabularnewline
8 & 2579.33333333333 & 390.916018261382 & 1482 \tabularnewline
9 & 2934.25 & 398.295487615094 & 1425 \tabularnewline
10 & 2679.5 & 348.175895985714 & 1333 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155535&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]2201.25[/C][C]308.694354573346[/C][C]1066[/C][/ROW]
[ROW][C]2[/C][C]2466.25[/C][C]322.77916036144[/C][C]1117[/C][/ROW]
[ROW][C]3[/C][C]2567.91666666667[/C][C]302.862542578262[/C][C]1142[/C][/ROW]
[ROW][C]4[/C][C]2601.58333333333[/C][C]258.022711591382[/C][C]884[/C][/ROW]
[ROW][C]5[/C][C]2588[/C][C]364.745490345354[/C][C]1204[/C][/ROW]
[ROW][C]6[/C][C]2572.33333333333[/C][C]275.379847857574[/C][C]944[/C][/ROW]
[ROW][C]7[/C][C]2449.91666666667[/C][C]372.260284877355[/C][C]1339[/C][/ROW]
[ROW][C]8[/C][C]2579.33333333333[/C][C]390.916018261382[/C][C]1482[/C][/ROW]
[ROW][C]9[/C][C]2934.25[/C][C]398.295487615094[/C][C]1425[/C][/ROW]
[ROW][C]10[/C][C]2679.5[/C][C]348.175895985714[/C][C]1333[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155535&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155535&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	2201.25	308.694354573346	1066
2	2466.25	322.77916036144	1117
3	2567.91666666667	302.862542578262	1142
4	2601.58333333333	258.022711591382	884
5	2588	364.745490345354	1204
6	2572.33333333333	275.379847857574	944
7	2449.91666666667	372.260284877355	1339
8	2579.33333333333	390.916018261382	1482
9	2934.25	398.295487615094	1425
10	2679.5	348.175895985714	1333

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	87.753941755503
beta	0.0961216979690282
S.D.	0.0858436621892522
T-STAT	1.11972969835696
p-value	0.295317561342619

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & 87.753941755503 \tabularnewline
beta & 0.0961216979690282 \tabularnewline
S.D. & 0.0858436621892522 \tabularnewline
T-STAT & 1.11972969835696 \tabularnewline
p-value & 0.295317561342619 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155535&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]87.753941755503[/C][/ROW]
[ROW][C]beta[/C][C]0.0961216979690282[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0858436621892522[/C][/ROW]
[ROW][C]T-STAT[/C][C]1.11972969835696[/C][/ROW]
[ROW][C]p-value[/C][C]0.295317561342619[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155535&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155535&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	87.753941755503
beta	0.0961216979690282
S.D.	0.0858436621892522
T-STAT	1.11972969835696
p-value	0.295317561342619

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	0.656155897435211
beta	0.655785906611222
S.D.	0.683418569852996
T-STAT	0.959566999697246
p-value	0.365372337381376
Lambda	0.344214093388778

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & 0.656155897435211 \tabularnewline
beta & 0.655785906611222 \tabularnewline
S.D. & 0.683418569852996 \tabularnewline
T-STAT & 0.959566999697246 \tabularnewline
p-value & 0.365372337381376 \tabularnewline
Lambda & 0.344214093388778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=155535&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]0.656155897435211[/C][/ROW]
[ROW][C]beta[/C][C]0.655785906611222[/C][/ROW]
[ROW][C]S.D.[/C][C]0.683418569852996[/C][/ROW]
[ROW][C]T-STAT[/C][C]0.959566999697246[/C][/ROW]
[ROW][C]p-value[/C][C]0.365372337381376[/C][/ROW]
[ROW][C]Lambda[/C][C]0.344214093388778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=155535&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=155535&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	0.656155897435211
beta	0.655785906611222
S.D.	0.683418569852996
T-STAT	0.959566999697246
p-value	0.365372337381376
Lambda	0.344214093388778

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 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