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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> par4 = '0.35'
> par3 = '13'
> par2 = '13.7808'
> par1 = '63'
> par1<-as.numeric(par1)
> par2<-as.numeric(par2)
> par3<-as.numeric(par3)
> par4<-as.numeric(par4)
> df <- par1 - 1
> if (par2 > par3)
+ {
+ myc <- par3 / df * qchisq(1-par4,df)
+ } else {
+ myc <- par3 / df * qchisq(par4,df)
+ }
> myc
[1] 13.77536
> 
> #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,hyperlink('http://www.xycoon.com/ht_variance.htm','Testing Variance - Critical value (region)','learn more about Statistical Hypothesis Testing about the Variance'),2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Sample size',header=TRUE)
> a<-table.element(a,par1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Sample variance',header=TRUE)
> a<-table.element(a,par2)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Null hypothesis (H0)',header=TRUE)
> a<-table.element(a,par3)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Type I error (alpha)',header=TRUE)
> a<-table.element(a,par4)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Critical value',header=TRUE)
> a<-table.element(a,myc)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Conclusion',header=TRUE)
> if (par2 > par3)
+ {
+ if (par2 < myc) a<-table.element(a,'There is no reason to reject the null hypothesis') else a<-table.element(a,'Reject the null hypothesis')
+ } else {
+ if (par2 > myc) a<-table.element(a,'There is no reason to reject the null hypothesis') else a<-table.element(a,'Reject the null hypothesis')
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/16riz1355871454.tab") 
> 
> 
> 
> proc.time()
   user  system elapsed 
  0.272   0.093   0.347