Statistics vs. Data Science

[Kevin Yeom]

Hello,

I am one of those who are joining the hype of data science and statistics. This year, I applied to several statistics, data science programs, and today, I received all notifications from the schools that I applied to.

Here is the list of schools that I applied and the status of each application

Duke Statistical Science Masters - accepted

Carnegie Mellon Masters in Statistical Practice - accepted

Columbia Masters in Data Science - accepted

New York Masters in Data Science - rejected

Columbia Quantitative Masters in Social Science - accepted

New York Masters in Applied Social Science Research - accepted

Penn State Masters in Applied Statistics - accepted

So, I am having a big problem in making a decision on which school to attend this fall. Part of me says that I want to join the data science hype and attend columbia, but unlike NYU program (which I got rejected), Columbia seems to be less flexible with its curriculum and with limited scope of learning material. Besides the machine learning course, I cannot find much difference between Columbia's data science program and Carnegie's master's in statistical practice program. Duke has fantastic statistics program, but I am not a big fan of suburb locality. 

What are the merits to attending data science program compared to attending traditional statistics program? 

Will people with data science degree have significantly better employment options than people with statistics degree?

QMSS also seems to be a neat program. I want to receive some feedback from fellow data scientists and statisticians!

 

[Tsilaeri]

Duke and CMU belongs in a different tier than the rest. I don't know why anyone would consider the other options than these two.

You can view data science as a collaboration of statistics and computer science.

Even the traditional statistics programs are slowly integrating with CS,

and it would be imperative for you to take couple of CS courses while in stats MS regardless of whether you'll go for employment or PhD.

In that sense, CMU that has no.1 CS department will have stronger synergy affect every year. It already has strongest statistics program among your list.

Duke is also strong choice, with top 10 statistics program, but since you don't like the locality I'd say CMU before Duke.

 

Then, there's the rest. 

 

Columbia DS is only a year or two old, I wouldn't risk going there considering that you already see its limits.

Moreover, you have no idea what their job placements will be like, and their stats department barely makes top 20.

Look if they offer financial aid other than standard FASFA aid, such as TA/RA ship or fellowship/scholarship.

If they don't, it is more likely that this program could be a cash cow for PhDs or its more research-focused degrees. 

The other three look like they're terminal degrees that would be more suitable for someone who would pursue PhD afterwards.

 

In summary, CMU. No brainer. If not, choose Duke even if you don't like its locality.

Edited April 3, 2016 by Tsilaeri

[GM1993]

Totally agreed, CMU is the best choice.  Data science in Columbia is not mature enough and sometimes regarded as a "Cash Cow" program because admissions to this program is not that competitive. QMSS is more like a preparation for further study in social science if you want to pursue PHD after your graduation.