R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> par5 = '0.9'
> par4 = '0.15'
> par3 = '0.95'
> par2 = '0.05'
> par1 = '20000'
> par5 <- '0.9'
> par4 <- '0.15'
> par3 <- '0.95'
> par2 <- '0.05'
> par1 <- '20000'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> (z <- abs(qnorm((1-par3)/2)) + abs(qnorm(1-par5)))
[1] 3.241516
> (z1 <- abs(qnorm(1-par3)) + abs(qnorm(1-par5)))
[1] 2.926405
> dum <- z*z * par4*(1-par4)
> dum1 <- z1*z1 * par4*(1-par4)
> par22 <- par2*par2
> npop <- array(NA, 200)
> ppop <- array(NA, 200)
> for (i in 1:200)
+ {
+ ppop[i] <- i * 100
+ npop[i] <- ppop[i] * dum / (dum + (ppop[i]-1)*par22)
+ }
> postscript(file="/var/fisher/rcomp/tmp/1731o1354461217.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(ppop,npop, xlab='population size', ylab='sample size (2 sided test)', main = paste('Confidence',par3))
> dumtext <- paste('Margin of error = ',par2)
> dumtext <- paste(dumtext,' Response Rate = ')
> dumtext <- paste(dumtext, par4)
> mtext(dumtext)
> grid()
> dev.off()
null device 
          1 
> (n <- par1 * dum / (dum + (par1-1)*par22))
[1] 521.9204
> (n1 <- par1 * dum1 / (dum1 + (par1-1)*par22))
[1] 427.4432
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Population Size',header=TRUE)
> a<-table.element(a,par1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Margin of Error',header=TRUE)
> a<-table.element(a,par2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Confidence',header=TRUE)
> a<-table.element(a,par3)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Power',header=TRUE)
> a<-table.element(a,par5)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Response Distribution (Proportion)',header=TRUE)
> a<-table.element(a,par4)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'z(alpha/2) + z(beta)',header=TRUE)
> a<-table.element(a,z)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'z(alpha) + z(beta)',header=TRUE)
> a<-table.element(a,z1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
> a<-table.element(a,n)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
> a<-table.element(a,n1)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/2rw6l1354461217.tab") 
> (n <- dum / par22)
[1] 535.8786
> (n1 <- dum1 / par22)
[1] 436.7562
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size (infinite population)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Population Size',header=TRUE)
> a<-table.element(a,'infinite')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Margin of Error',header=TRUE)
> a<-table.element(a,par2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Confidence',header=TRUE)
> a<-table.element(a,par3)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Power',header=TRUE)
> a<-table.element(a,par5)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Response Distribution (Proportion)',header=TRUE)
> a<-table.element(a,par4)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'z(alpha/2) + z(beta)',header=TRUE)
> a<-table.element(a,z)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'z(alpha) + z(beta)',header=TRUE)
> a<-table.element(a,z1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size (2 sided test)',header=TRUE)
> a<-table.element(a,n)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Minimum Sample Size (1 sided test)',header=TRUE)
> a<-table.element(a,n1)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/346b11354461217.tab") 
> 
> try(system("convert tmp/1731o1354461217.ps tmp/1731o1354461217.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.891   0.250   1.121