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*The author of this computation has been verified*

R Software Module: /rwasp_smp.wasp (opens new window with default values)

Title produced by software: Standard Deviation-Mean Plot

Date of computation: Sun, 13 Dec 2009 09:27:54 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh.htm/, Retrieved Sun, 13 Dec 2009 17:29:45 +0100

BibTeX entries for LaTeX users:

@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

462 455 461 461 463 462 456 455 456 472 472 471 465 459 465 468 467 463 460 462 461 476 476 471 453 443 442 444 438 427 424 416 406 431 434 418 412 404 409 412 406 398 397 385 390 413 413 401 397 397 409 419 424 428 430 424 433 456 459 446

Output produced by software:

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	'Gwilym Jenkins' @ 72.249.127.135

Standard Deviation-Mean Plot
Section	Mean	Standard Deviation	Range
1	459.75	3.20156211871642	7
2	459	4.08248290463863	8
3	467.75	7.84750491132904	16
4	464.25	3.77491721763537	9
5	463	2.94392028877595	7
6	471	7.07106781186548	15
7	445.5	5.06622805119022	11
8	426.25	9.10585891976516	22
9	422.25	12.8679187646384	28
10	409.25	3.77491721763537	8
11	396.5	8.66025403784439	21
12	404.25	11.056672193748	23
13	405.5	10.6301458127346	22
14	426.5	3	6
15	448.5	11.7331439378654	26

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha	32.8812891116887
beta	-0.0591243661737563
S.D.	0.0335162872357342
T-STAT	-1.7640487968703
p-value	0.101193344711179

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha	24.5255032408143
beta	-3.73534739810546
S.D.	2.26565665380093
T-STAT	-1.64868202418886
p-value	0.123155552179332
Lambda	4.73534739810546

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh/1s3gz1260721670.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh/1s3gz1260721670.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh/27q811260721670.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/13/t1260721783rz250gfp90hbbjh/27q811260721670.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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