SPSS: 2 sample t-test: real data against fictional group with M=0 and SD=1? We want to use SPSS to compare two groups (2 independent samples t-test). The first group contains real data, the other group is fictional. This fictional group should contain as many "subjects" as the real (1st) group. But the mean is set to 0 and the standard deviation to 1 (standard normal distribution).
There are several tools out there to compare two groups by adding the number of subjects, mean and std for every group independently. But how can we do this in SPSS? I only know how to test one variable (group1) against a test value (T=0).

EDIT:
Here a more detailed description of why I wanted to use this two-sample t-test, although this kind of approach seemed strange to me in the beginning. The thing is that we investigated 20 patients and compared their data with a large database of healthy control subjects. That means we did a z-transformation using the reference database (standard procedure in this field (quantitative sensory testing,QST)). 

There are other research groups which suggest to then use the 2-sample t-test I mentioned below, because it would be inappropriate to compare data of 20 patients with data of 1200 controls. So they invented a fictional group with M = 0 and SD = 1 and tested the real data against this fictional data (on a website like this --> but Two-Sample T-Test). This approach would be more conservative than using the one-sample t-test with test value=0.
To be honest, I have no idea if this is the right approach. My first idea was to do a one-sample t-test and test the patient group (i.e. their z-values) against the value 0 to see, whether the z-values differ significantly from 0 instead of using a fictional dataset.
 A: If you want to see if the first group fits a N(0,1) distribution, why not just do a goodness of fit test instead of creating an artificial N(0,1) data set to compare it with?  Although what you suggest doing is unconventional it is possible to do the two-sample t-test to see if the means are equal (essentially both 0).  Of course, you might say that if the goal is to test for 0 mean why not just do the one sample test that the mean is zero rather than create the artificial second sample (which induces additional uncertainty and reduces the power of the test)?  It seems that alternative approaches provide better choices.
A: Unlike statistical calculators (such as the one you link to) where you can input summary statistics' values, SPSS needs original data as input. So, if you really insist on two-sampe, not one-sample t-test, you have to create case-wise data for the second group. Since you know independent-sample t test depends on just 3 things, the mean, the st. deviation and the sample size, any sample with these statistics defined will do for you. So, you may just take your 1st sample, standardize it (in Descriptives menu) to obtain mean 0 and st. deviation 1, and paste these data below the sample 1 data as sample 2 data. Then proceed to independent-sample t-test menu.
