gc2012

First, I agree with previous replies, you'd be a much stronger applicant if you could increase your GRE quant score 4+ points. I realize that is much easier said than done. 
However, if you were able to increase your score to 165+, I feel like previous replies are a little pessimistic. With a reasonably strong GRE, my guess is lack of real analysis would not prove to be such a problem. As a point of clarification, there are PhD students at UNC who have not taken real analysis. Most have taken it, but off the top of my head, I can think of a handful without that background. My sense is those students got in on the strength of their letters of recommendation and research background. I doubt programs like Vanderbilt, BU, Penn, etc. would be materially different.
To the point about programs not caring about applied research/work experience, I do not think that is true in general. If your research/work experience demonstrates your potential as a independent researcher, it can be a strength of your application, particularly if it leads to very strong letters from your supervisors (ideally stat/biostat PhD supervisors).

First, I agree with previous replies, you'd be a much stronger applicant if you could increase your GRE quant score 4+ points. I realize that is much easier said than done. 
However, if you were able to increase your score to 165+, I feel like previous replies are a little pessimistic. With a reasonably strong GRE, my guess is lack of real analysis would not prove to be such a problem. As a point of clarification, there are PhD students at UNC who have not taken real analysis. Most have taken it, but off the top of my head, I can think of a handful without that background. My sense is those students got in on the strength of their letters of recommendation and research background. I doubt programs like Vanderbilt, BU, Penn, etc. would be materially different.
To the point about programs not caring about applied research/work experience, I do not think that is true in general. If your research/work experience demonstrates your potential as a independent researcher, it can be a strength of your application, particularly if it leads to very strong letters from your supervisors (ideally stat/biostat PhD supervisors).

First, I agree with previous replies, you'd be a much stronger applicant if you could increase your GRE quant score 4+ points. I realize that is much easier said than done. 
However, if you were able to increase your score to 165+, I feel like previous replies are a little pessimistic. With a reasonably strong GRE, my guess is lack of real analysis would not prove to be such a problem. As a point of clarification, there are PhD students at UNC who have not taken real analysis. Most have taken it, but off the top of my head, I can think of a handful without that background. My sense is those students got in on the strength of their letters of recommendation and research background. I doubt programs like Vanderbilt, BU, Penn, etc. would be materially different.
To the point about programs not caring about applied research/work experience, I do not think that is true in general. If your research/work experience demonstrates your potential as a independent researcher, it can be a strength of your application, particularly if it leads to very strong letters from your supervisors (ideally stat/biostat PhD supervisors).

It's a big program, we seemingly know different people. Most of the people I know in the program have stayed on with the faculty academic advisor to whom they were assigned when they came in. I also would agree that most of them are satisfied with their advisors. That being said, it's clearly a debatable point and a bit of a semantic argument, but I still argue that the student/advisor pairing is far more related to faculty preferences than students. And I think it's misleading to suggest that any student can simply choose to work with any advisor. 
Second, I think it's valuable to be clearer about what 'guaranteed' funding means. I also have, in writing, 'guaranteed' funding. However, that does not mean the department has a specific grant designated to fund me throughout the rest of my time in the program (they might have this for some students). Rather, I've had year to year GRA appointments, and at the end of each year, I have to talk to the student service managers, they send out my CV to the faculty and other affiliated researchers, and I hope that something comes through. This has worked out thus far, but it's stressful and it's not clear what would happen if nothing materialized. Other students, I think, have more stable sources of funding, but at least in my case, this is 'guaranteed funding' at UNC. 
Also on that note, it varies wildly by GRA as to whether you will be asked to work 20 hours per week. If your GRA advisor is kind and can afford to pay you for nothing, you might only have to work a few hours per week. However, they are fully within their rights to demand 20 hours of work per week (I have had these types of GRAs), and I know people who have had GRAs where the researcher basically bullied them into working more than 20 hours. I don't think that's common, but it's common enough that student service managers have to intervene (and brought it up to me, unsolicited). Sometimes a 20 hour GRA is workable, but other times (like your qual year), it isn't. 
Last, again a matter of opinion, I wouldn't say the data science curriculum is a particularly noteworthy feature of the program. Basically they now require first year students to take an introductory course in R and (a little python) instead of SAS (which was previously required, and still heavily used in core courses). The precision medicine and statistical computing courses are newer, so I can't speak to them. I would note that they are electives and therefore might not be offered every year (although I think they plan to do so for computing). 
 
 
 
 

It's a big program, we seemingly know different people. Most of the people I know in the program have stayed on with the faculty academic advisor to whom they were assigned when they came in. I also would agree that most of them are satisfied with their advisors. That being said, it's clearly a debatable point and a bit of a semantic argument, but I still argue that the student/advisor pairing is far more related to faculty preferences than students. And I think it's misleading to suggest that any student can simply choose to work with any advisor. 
Second, I think it's valuable to be clearer about what 'guaranteed' funding means. I also have, in writing, 'guaranteed' funding. However, that does not mean the department has a specific grant designated to fund me throughout the rest of my time in the program (they might have this for some students). Rather, I've had year to year GRA appointments, and at the end of each year, I have to talk to the student service managers, they send out my CV to the faculty and other affiliated researchers, and I hope that something comes through. This has worked out thus far, but it's stressful and it's not clear what would happen if nothing materialized. Other students, I think, have more stable sources of funding, but at least in my case, this is 'guaranteed funding' at UNC. 
Also on that note, it varies wildly by GRA as to whether you will be asked to work 20 hours per week. If your GRA advisor is kind and can afford to pay you for nothing, you might only have to work a few hours per week. However, they are fully within their rights to demand 20 hours of work per week (I have had these types of GRAs), and I know people who have had GRAs where the researcher basically bullied them into working more than 20 hours. I don't think that's common, but it's common enough that student service managers have to intervene (and brought it up to me, unsolicited). Sometimes a 20 hour GRA is workable, but other times (like your qual year), it isn't. 
Last, again a matter of opinion, I wouldn't say the data science curriculum is a particularly noteworthy feature of the program. Basically they now require first year students to take an introductory course in R and (a little python) instead of SAS (which was previously required, and still heavily used in core courses). The precision medicine and statistical computing courses are newer, so I can't speak to them. I would note that they are electives and therefore might not be offered every year (although I think they plan to do so for computing). 
 
 
 
 

I guess just to clarify, I'm not saying you will have zero agency regarding your dissertation advisor at UNC, it will just be limited. Possibly more so than other programs, but I can't really speak to that. Moreover, for better or worse, if you come to UNC biostat, if you pass your quals, you will probably be so relieved that you won't really care about who you work with for your dissertation. I'm not saying that's a positive trait, but I think a large number of students in the program would say the same thing. 

@little white in Stat So the way it works is when you come to UNC biostat, you will get an academic advisor and a research advisor. Sometimes these are the same, but they are often not. The academic advisor will be biostatistics faculty, the research advisor may not be (i.e., they might be an MD with a grant for which you help provide statistical support). The work you do for your research advisor is what funds your stipend and tuition. That work is often statistical programming for some scientific study, not statistical methods development. You will meet with this person once a week.  
The academic advisor is (theoretically) the person with whom you will do your thesis research, but you likely won't have a lot of interaction with that person until (or if) you pass your qual. You don't initially choose this person, you are just assigned to someone. I believe the faculty review the application materials of all the incoming PhD students and divide them up. I suspect they try to match the research interests expressed in your application essay to an appropriate faculty member, but it's not a guarantee, and nobody will directly ask your opinion. 
Once you pass your qualifier, you theoretically could change academic advisors, but in practice I think many/most students just stick with their originally assigned person. If you do want to change, you would have to work it out with the faculty members in question. There isn't really a set way to do that, it's kind of ad hoc. For instance, where some programs like Penn have research rotations (i.e., 1-2 month periods where you work with different faculty members and then choose one at the end), we do not. And when it comes to faculty like Danyu Lin, Michael Kosorok, Joe Ibrahim, etc., basically everyone in the program would like to work with them so you can't just 'choose' them, you can express interest in their work, and they decide whether to take you (which for those 3 is not overly likely due to existing volume). 
 
 

I can't fully answer your question, but I'm a current UNC biostat student, so I can offer a few clarifications about the program. First, (basic) measure theory is covered for one month, there is one test over the material (and measure theory is only half of the tested material), and then it's never brought up again (even on the qualifier). So I wouldn't go to UNC with the idea that you will get a lot of instruction in measure theory. I don't know anything about Duke, but for Duke stat to have less measure theory than UNC biostat, they would basically have to not cover it at all. 
Second, if you go to UNC, don't expect to do meaningful statistical research until after you pass your qualifying exam, which will be after 2 years if you come in without a relevant Master's (and if you pass on the first try). A small handful of students do a little bit of statistical research prior to passing their qual, but by and large, you basically won't do any work towards a thesis until passing. You will probably have to do some statistical programming for an applied project (i.e. GRA or training grant), but it's typically not the same as thesis work.
Third, this is more of a feeling than a hard and fast rule, but it seems to me that students don't really choose their faculty research advisor, the faculty choose their research students. So I wouldn't count on working with any specific research advisor at UNC. Also, for the higher profile faculty, they do tend to have a lot of students, and so many of them co-advise their research students along with a more junior faculty member with fewer time demands. 

I can't fully answer your question, but I'm a current UNC biostat student, so I can offer a few clarifications about the program. First, (basic) measure theory is covered for one month, there is one test over the material (and measure theory is only half of the tested material), and then it's never brought up again (even on the qualifier). So I wouldn't go to UNC with the idea that you will get a lot of instruction in measure theory. I don't know anything about Duke, but for Duke stat to have less measure theory than UNC biostat, they would basically have to not cover it at all. 
Second, if you go to UNC, don't expect to do meaningful statistical research until after you pass your qualifying exam, which will be after 2 years if you come in without a relevant Master's (and if you pass on the first try). A small handful of students do a little bit of statistical research prior to passing their qual, but by and large, you basically won't do any work towards a thesis until passing. You will probably have to do some statistical programming for an applied project (i.e. GRA or training grant), but it's typically not the same as thesis work.
Third, this is more of a feeling than a hard and fast rule, but it seems to me that students don't really choose their faculty research advisor, the faculty choose their research students. So I wouldn't count on working with any specific research advisor at UNC. Also, for the higher profile faculty, they do tend to have a lot of students, and so many of them co-advise their research students along with a more junior faculty member with fewer time demands. 

Yeah, @galois makes a number of good points. When considering a PhD, I think it's important to consider the long term trajectory of your career. Right now, having a bachelor's is enough to get the job you want, but no matter how well paid/prestigious the position is, it's still an entry level job and you will eventually get bored and want a more challenging position. At some point, not having an advanced degree will likely limit your career advancement. Of course this is not the case uniformly across companies, but why take the chance? I do think it's reasonable to take the job, see how it goes, and then reapply to graduate programs in the future. However, as someone who worked and then went back to school, I reiterate the points above, it just gets harder and harder to be an underpaid, overworked graduate student as you get older. Ultimately, if you think you will eventually want a PhD (which seems likely), I think you would be happier if you start now and finish by the time you are 27 or 28.  

To the extent this affects your career decisions, I'd like to push back on some of the previous comments. I certainly agree that it is possible to have an academic career in biostatistics regardless of specific PhD program. I personally know (non-tenure track) faculty who trained at non-prestigious institutions. However, I don't think it's reasonable to suggest the rank of your program is inconsequential. Clearly, there is a correlation/causation issue, but in general, I think the likelihood of obtaining an academic position post-graduation will be lower for students from lower ranked programs. Moreover, I don't take it as self-evident that advisor matters more than program, but even if we accept that claim, program ranking largely reflects the strength of the faculty. Thus, there are fewer well known researchers at less prestigious programs. Of course there are exceptions, but my point is, I wouldn't hang my hat on going to a low ranked institution, working with a prestigious advisor, and going on to a prestigious faculty position. That scenario is possible, but I think the much more likely outcome would be work in government or industry. 

You would be much better off with the stat prof as long as the letter is somewhat strong. Also, there is no reason for you to speculate on whether that's the case, it's perfectly reasonable to ask point blank, 'are you willing and able to write a strong letter of recommendation for me'?  If not, then ask the history prof the same question. 

You would be much better off with the stat prof as long as the letter is somewhat strong. Also, there is no reason for you to speculate on whether that's the case, it's perfectly reasonable to ask point blank, 'are you willing and able to write a strong letter of recommendation for me'?  If not, then ask the history prof the same question. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I think it's valuable to think about your long term goals here. Keep in mind, your institution and degree program (statistics/biostatistics) will be at the top of your CV for the rest of your life. It will be the first thing every hiring committee sees. That aside, I don't think it's unreasonable to assume that going to a biostatistics program puts you on a track to become faculty in a biostatistics department, and a statistics program points you to positions in statistics departments. Obviously that is not true in every case, but it's a reasonable rule of thumb. I do agree that its easier to go from statistics to biostatistics than the other way around. 
The other key thing to consider, at least about biostatistics, is that it is very applied in practice. To be sure, there are very high profile academic biostatisticians doing fairly theoretical work, but the vast majority of practicing biostatisticians spend a large amount of time providing statistical support to biomedical researchers. Moreover, methods development in biostatistics will require learning a lot about the underlying science. For instance, if you work in statistical genetics, you need to know a lot about genetics. I don't know enough about regular statistics professors to comment on whether they have similar experiences, but my suspicion is there is less of an applied aspect. 
As to the salary issue, let's be precise. Amstat news regularly produces a salary survey and biostat professors report making about $20,000 more than stat professors of equal experience. It is true that the salaries for statistics faculty are for 9 month contracts, compared to 12 months for biostatistics. To be clear, though, a 9 month salary means that stat professors are only contractually obligated to work for 9 months,  but they also aren't paid at all for the remaining 3 months of the year. So at the end of the day, that 9 month salary is what they get in institutional support over 12 months. So the distinction here is that biostatistics faculty are required to work more, but they do in fact get paid more on an annual basis. 
With regard to biostatisticians having to get most of their salary support from grants, that is true, but with some important caveats. Namely, it's easier for biostatisticians to get grants than most other scientists. Basically, the way it works for most biostat faculty is they spend a fairly large amount of time writing the statistics sections of grant applications for biomedical researchers. They get in on enough of these grants that when even a few of them go through, they have salary support. So if working on grant applications does not appeal to you, think very hard about going into biostatistics at an academic institution. However, for those willing, obtaining salary support via grants is not so scary. 

I'm a current student, let me clarify. I have guaranteed funding. I expect most other PhD students in the program have guaranteed funding. Even some of the Master's students have funding. I obviously don't know about every student's funding status, so there may a small number of PhD students who do not have it. However, UNC biostatistics absolutely does guarantee funding explicitly. They will send you a letter specifying your exact stipend and the number of years they will guarantee it. As I recall, the funding letter came shortly before the visit day. If you don't get a letter specifying your funding, you don't have guaranteed funding. 
As to the tuition waiver, it's not something to worry about. Your first year funding covers out of state tuition. After the first year, you will have lived in North Carolina long enough to establish residency and therefore will be eligible for in state tuition. Getting in state residency requires submitting a few forms to the state. You be reminded many times by the department to do this.  

I'm a current student, let me clarify. I have guaranteed funding. I expect most other PhD students in the program have guaranteed funding. Even some of the Master's students have funding. I obviously don't know about every student's funding status, so there may a small number of PhD students who do not have it. However, UNC biostatistics absolutely does guarantee funding explicitly. They will send you a letter specifying your exact stipend and the number of years they will guarantee it. As I recall, the funding letter came shortly before the visit day. If you don't get a letter specifying your funding, you don't have guaranteed funding. 
As to the tuition waiver, it's not something to worry about. Your first year funding covers out of state tuition. After the first year, you will have lived in North Carolina long enough to establish residency and therefore will be eligible for in state tuition. Getting in state residency requires submitting a few forms to the state. You be reminded many times by the department to do this.  

I'm a current student, let me clarify. I have guaranteed funding. I expect most other PhD students in the program have guaranteed funding. Even some of the Master's students have funding. I obviously don't know about every student's funding status, so there may a small number of PhD students who do not have it. However, UNC biostatistics absolutely does guarantee funding explicitly. They will send you a letter specifying your exact stipend and the number of years they will guarantee it. As I recall, the funding letter came shortly before the visit day. If you don't get a letter specifying your funding, you don't have guaranteed funding. 
As to the tuition waiver, it's not something to worry about. Your first year funding covers out of state tuition. After the first year, you will have lived in North Carolina long enough to establish residency and therefore will be eligible for in state tuition. Getting in state residency requires submitting a few forms to the state. You be reminded many times by the department to do this.