The dist of 0 vs 1 is documented as being slightly skewed (.05%) toward 1s. If the RNG chips aren't too expensive, you could take the output from 2 (or more) of them and XOR the outputs together to reduce skew.
There are all sorts of statistics you can look at that may help you understand the quality of the randomness you're getting. One of the central concerns is finding the underlying patterns and the random noise driving them, though in this case we're looking for the noise and dumping the patterns rather than the opposite. Some things that are good to look at are first and second differences of the series (e.g. take Y1=X2-X1, Y2=X3-X2, ... and Z1=Y2-Y1, Z2=Y3-Y2... and on up for higher differences) and look for distributions and patterns there. You may also want to look at moving averages (take a window of K samples and slide that through the sample space, for several values of K.) This stuff is similar to Fourier-series analysis for discrete-valued data. If you want to read lots of gory details on the math, the book by Box and Jenkins on Time Series Analysis was one of the best textbooks ~20 years ago. As my professor put it, if you stare at the numbers long enough, you can find all sorts of things in them, which may or may not really be there :-) # Thanks; Bill # Bill Stewart, stewarts@ix.netcom.com, +1-415-442-2215