On Thu, Nov 8, 2012 at 12:17 PM, David A. <dasolexa at hotmail.com> wrote:
In R:
normal200<-rnorm(200,0,1)
You forgot set.seed(310366) so we can reproduce your random numbers exactly.
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:
Is SPSS just estimating the 95th percentile from your data? Regardless of any distribution? Like R's quantile(normal20,0.95)? I get much closer answers to your SPSS using R for that, and I suspect one of the 9 quantile algorithms will give an exact answer (unless SPSS uses something else entirely). Whereas qnorm in R is giving you the 95th percentile of a Normal distribution with a given mean and sd. Barry