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I plan to be applying to graduate school next year in Statistics or Biostatistics and due to some financial constrictions, I will not be able to attend unless the tuition is waived at the the minimum. I am hesitant to commit to a 5 year PhD program for a funded education since I may run into some financial issues a few years in and may not be able to complete it. I know that most schools use their Masters program as a cash cow and thus are usually not funded. I was wondering if anyone here knew of any statistics programs that go against this and actually do fund their Master students?

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Apply to PhD programs that can or will award a master's degree after you pass your qualifiers.

This way you have funding and you may find that the funding is enough to continue even if other financial constrictions happen. You don't know for sure that they will happen or that other circumstances may mitigate the problem.

It might also be possible to ask the department for a leave of absence (for a year or two).

In a worst case scenario, hopefully you can finish with a master's.

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    I don't think that advising someone to take up a PhD program solely for the purpose of funding a MS degree is constructive advice. – Shion Feb 26 '14 at 18:24
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    I'm not. OP doesn't say that he/she knows for sure that he'll have funding problems later. I saying (badly I guess) go ahead and deal with later financial problems...later. – mkennedy Feb 26 '14 at 19:19
  • A leave of absence during a PhD is very possible, some places will allow leaves in the 2-4 year range. Sometimes you can still work on your PhD while taking a leave of absence and defend immediately after returning. – WetlabStudent Feb 27 '14 at 3:57
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Funding problems can come up in PhD programs regardless as to whether you expect them. For example, students who take more than 4-6 years often are given lower priority for department TA-ships, and lose their funding. The message here is that it is hard to predict your financial situation, and leaving a PhD for under extreme financial circumstances is always a morally acceptable thing to do (leaves of absences are very possible in this situation). You should do a PhD if you are truly passionate about pushing the envelope in statistics. In other words you think about statistics for fun. If this fits you, you should accept a funded PhD offer regardless as to future financial situations that may or may not manifest. Now if you are not passionate enough about the subject to pursue a PhD that is another story. In this case persuing one just because it is "free" and dropping out with a masters is generally looked upon as a major faux pas.

However, if you don't have interest in a PhD, another option would be to try online masters programs which are often cheaper and allow you to finish the degree while doing part time or in some cases even full time work. With an online degree program you can live with family members or move to a city with a low cost of living. The University of Washington has a program in data science, I believe. It certainly isn't free, but its about an order of magnitude less than a traditional "cash cow" masters degree.

If the above are too expensive take some free MOOCs (corsera etc) in your field of interest. Focus on skills as opposed to a degree. Apply for some jobs and if you don't get anything, go back to the drawing board.

The other option, and probably the best one if you are lucky enough to be successful down this road is to get a job in a field the combines your skill set with the tools you want to learn. So if you have some background in data science, stats, math or engineering, consider looking for jobs as opposed to degree programs. Often these jobs will fund your masters degree later on, if you choose go back to school. It generally comes with a constraint where you agree to stay with the company for at least a year or two after attaining the degree, but for most people this is worth it.

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You should look for schools that don't offer PhD's in statistics, only master's. Then they will hire their MS students as statistics TA's.

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