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galois

Is the adage regarding MS vs PhD true in Statistics?

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I'm sure we're all familiar with the countless tales of PhD depression, drop out, mental health issues, etc. caused by entering into a PhD for the wrong reasons, whether that be for job prospects, social status, or what have you, instead of the correct reason: passionate desire to produce novel research in a particular field.

Do you guys think this applies to the field of Statistics? I ask for myself, and also because I notice many posts relaying the same thoughts that I have: indecision between MS and PhD due to cost of MS.

If I'm honest with myself, if MS programs were typically funded, I would much rather commit myself to just two years and then see how I feel afterwards. Does this mean I should reevaluate applying to PhD programs?

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A lot of students enter PhD programs (and other professions like medicine, law, etc.) for the perceived social status, because they were "good at school" and they figured the PhD program would be an extension of undergrad, and for the job prospects. I do think that the attrition rate does tend to be higher for those students in most disciplines, including Statistics. 

I think it's okay to want to do a PhD for the improved job prospects and the status (admittedly, in some fields like CS and statistics, having a doctorate *does* confer higher earning potential... and if you're more picky about the areas you want to work on, then having a PhD is helpful). But one should be cautioned about a number of things:

- having a PhD =/= automatic respect for your opinions. As with anything, respect has to be earned, and reputation takes many years to build up. A PhD makes you a mini-expert in a very specific area of study, and people will rarely assume that this makes you an authority on other matters. So you should definitely do it because you personally want to do it for your own fulfillment, not because you think others will have a much higher opinion of you. 

- be aware that it is a lengthy time commitment and that there is high opportunity cost. So unless you can tolerate the idea of spending 4-6 years on it, earning $30k or less, you might be better off getting a Masters and/or working full-time.

- the PhD is ultimately about producing an independent researcher. Grades don't really matter in a PhD program, as long as they are above a 3.0 GPA (in order to keep your funding). Moreover, research is not at all like studying for a test. It's about repeatedly trying different approaches to tackle a problem, encountering numerous failures and setbacks, and learning when to give up and move on. Even after you've completed research and written manuscripts, it's likely that some or all of your papers will be met with rejection from journals or conferences. For the straight-A students who are used to acing all their classes and being the top student, a PhD can therefore be very demoralizing and disorienting. That's why I think it's a good idea for bright students to know what they are getting into and to be mentally prepared for failure and rejections. After awhile, you just get used to it and learn how to keep going in the face of failure/rejection, but for students who haven't encountered this a lot before in their academic careers, it can be very disheartening.

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One thing that influenced my decision:

 

Even though statistics and data science are the hot thing right now, do I really want to wait 5+ years to enter the field? I've already experienced starting school when a field was hot and graduating (with no work experience) after it was saturated. I'm not willing to go through that again so I'm going to work for a few years after getting my masters and then evaluate where I am at. 

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Interesting thoughts from both of you, and a good things to keep in mind. Thanks.

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I would add to dmacfour's comment that apart from academia, a PhD is useful for getting jobs as Research Scientists, positions which are typically not available to those with only Masters. The department where I earned my doctorate has PhD grads employed as research scientists at Amazon, Siemens, etc. working in areas like machine learning and AI. The PhD trains you to be a researcher.

If you just want to learn some current machine learning methods and get a job quickly, then a Masters is the way to go (and sometimes that isn't even necessary -- I have a friend who only got a Bachelor's in Biochemistry but then he self-taught himself all the programming and machine learning tools to break into the field of data science). These jobs can also be interesting and you can learn new methodologies/programming hacks/etc. on the job.

Edited by Applied Math to Stat

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