[R] difference percentile R vs SPSS

[Duncan Murdoch]

On 12-11-08 7:17 AM, David A. wrote:
>
> Dear list,
>
> I am calculating the 95th percentile of a set of values with R and with SPSS
>
> In R:
>
>> normal200<-rnorm(200,0,1)
>> qnorm(0.95,mean=mean(normal200),sd=sd(normal200),lower.tail =TRUE)
> [1] 1.84191
>
> In SPSS, if I use the same 200 values and select Analyze -> Descriptive Statistics -> Frequencies
>
> and under "Statistics", I type in '95' under Percentiles, then the output is
>
> Percentile 95      1.9720
>
>
>
> I think the main difference is that SPSS only calculates critical values within the range of values in the data, while R fits a normal and calculates the critical value using the fitted distribution. This is more obvious if the size of the data is much lower:
>
>> normal20
>   [1]  0.27549020  0.87994304 -0.23737370  0.04565484 -1.10207183 -0.68035949  0.01698773 -2.15812038  0.26296513  0.21873981  0.03266598 -0.01318572
> [13]  0.83492830  0.54652613  0.73993948 -0.31937556 -0.03060194 -0.96028421  0.27745331 -1.01292410
>> max(normal20)
> [1] 0.879943
>> qnorm(0.95,mean=mean(normal20),sd=sd(normal20),lower.tail =TRUE)
> [1] 1.118065
>
> And in SPSS
>
> Percentile 95     0.8777
>
>
>
> Can anyone comment on my statement? and thus, is R more exact? The differences are quite large and this is important for setting thresholds.

The part of your statement where you say "R fits a normal and calculates 
the critical value using the fitted distribution" is false.  *You* did 
that (in your call to qnorm, rather than using the  quantile function), 
it's not something R would normally do.

Is R "more exact"?  It's possible, but I doubt it.  I imagine SPSS could 
do what R did, and R could do what SPSS did.

Duncan Murdoch