MrKrabs3

If you are contemplating getting a PhD in Statistics and your profile is competitive enough *without* the Masters, then I would recommend just applying directly to PhD programs.
But if you do insist on going the Masters route first, then the Masters in Statistics (or in Math/Applied Math where you can take the stats classes) would be the best preparation for a Statistics PhD program. For one, it might save time later as far as fulfilling coursework requirements -- you might be able to place out of all the first year classes. I have a MS in Applied Math but I took 4 statistics classes in my MS program, including both semesters of Casella & Berger and the applied statistics classes. As a result of this, I decided to try my PhD department's qualifying exam upon arrival (after spending maybe hundreds of hours practicing old qualifying exam questions), and I passed it so I was able to skip all the first year classes. That saved some time as far as degree completion. 
But even if you do repeat the first-year classes (applied stats and theoretical stats sequences) once you enter a PhD program, you will be completely prepared because you will have seen the material previously. 

You do not have to commit to doing the PhD. You can enter the PhD program and leave with a master's. It's becoming more and more common.
Also, 4 years for a PhD (especially without a master's) is very fast. It's more like 5-6 years.

I think your GRE score is perfectly fine, actually. A 170 on the verbal is also impressive, as most applicants to Stat PhD programs do not score nearly this well. The Q score of 164 is also fine -- I wouldn't bother to retake it.

While Statmaniac has made some valid points, methinks that they have extrapolated a bit too much based on their personal research. For example, they dismiss detailed study of GLM's, but argue that information theory and functional analysis are things that are "more important and fundamental to learn." Many stat students can get by and publish in top journals/conferences without having taken an entire course on information theory or functional analysis -- they can pick up on the things from these areas that they need for their research *if* they ever need it (like the various entropies and divergences, for example). And students who are doing more applied statistics have little use for those subjects. Anyway, it is a matter of opinion what is "most important and fundamental."  

I wouldn't call it safe but it's definitely reasonable to apply to schools like that with your profile. 

Sorry for getting distracted. I think your estimate of 30-60 is pretty accurate.

Oh, I was not aware of this at all. In any event, if the OP applies to programs at large state schools like TAMU, UMinnesota, etc., they might be able to get in. I have known people who got their PhDs from TAMU and UMN (and are now TT faculty at R1s) who did their undergrad at places like Central Michigan University or Southern Illinois University. I think **domestic** students from these regional schools with high GPAs stand a reasonable chance at most of the Stat PhD programs ranked 20-40 by USNWR.

Unfortunately many of the UC stats programs don’t like to take CSU students.  I think it is unfair for a variety of reasons. You should be aware of this bias so you can counter it   Maybe some of the other posters have suggestions

California students get automatic in state tuition, so if anything I would imagine the department could saving money by taking California students. What reason would they possibly have for having something against CSU students versus any other middle of the road state school?

I think your profile is good enough to get into UC Irvine. UCLA and UC Davis are also attainable for your profile.
I don't think top 30-60 is a reach at all, and you may even be able to get into some top 20 schools as well (big state schools like Iowa State and TAMU seem like a good bet -- and possibly University of Minnesota as well).
Consider taking one or two more upper division math classes this fall, and you should be good to go.