Masters in Statistics vs in data science? Is DS just buzz?

In summary, the terms "statistics" and "data science" encompass a lot of skills and it's important to look past the labels and focus on the specific skills gained in each program. While most MS students in statistics know how to program, the quality of data science programs may be highly variable. Internship opportunities and careful examination of program requirements are important factors to consider when choosing between an MS in statistics or an MS in data science. Additionally, having a variety of skills, including programming, is becoming increasingly important in the field of data analysis.
  • #1
annoyinggirl
218
10
which do you think is the smarter choice, in terms of employ-ability: ms in statistics or Ms in data science? do you think "data science" is just a buzz words that will die out? is a data scientist someone who can't program as well as the computer engineer, and can't build models as well as a statistician - a jerk of all trades, master of none? And is a jack of all trades a favorable trait to have in data analysis, esp in the age of computers? Or do you think people will realize that it is best to have statisticians build the models and then have programmers do the programming? But are not most statistics models just overkill for industry? programming skills are more important today in data analysis?
 
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  • #2
I'd advise looking past the words/labels and looking at the underlying skills. The words "statistics" and "data science" both encompass a lot of things, and probably more than they should.

I do think everyone needs to know how to code, even if it's in a fairly high level language.
 
  • #3
annoyinggirl said:
Or do you think people will realize that it is best to have statisticians build the models and then have programmers do the programming?

That isn't necessarily the best organization. In fact, only in a very large or a very bureaucratic organization would there be designated programmers who only have the responsibility of programming.

That organization might have been common in the old days - when it was also best for the technical staff to write their reports in long hand and for the secretarial pool to type them.

A situation where I have seen programmers who only program is when a contractor is executing a contract with a large organization (e.g. a US government organization) and the contract specifically states that the contractor is only responsible for providing programming services. In that case, programmers for the contractor can refuse to do analytical work and demand detailed specifications for what they are supposed to implement.

I've met programmers who feel this is only "professional" way to operate. Years ago, I knew analyists who felt it was beneath their dignity to program. However, nowadays I think it's best is to have employees who can tackle a variety of jobs - analyze, program, pack boxes when the firm moves to a new office, etc.
 
  • #4
I would agree with Locrian and Stephen Tashi that it's important to look past the labels and focus more on the specific skills you gain in either program.

What I can tell you is that most MS students in statistics (including myself) know how to program (as well they should), and certainly during my career have programmed and built statistical models in a variety of different career areas (currently working in the pharma/biotech sector). The MS program in statistics should provide an option for students to take computer-intensive and applied courses in addition to the more mathematical courses.

My concern about the data science MS program is that the degree is still relatively new, and the quality of the data science MS programs may be highly variable. And at the end of the day, I'm not sure you'll necessarily end up with a skill set in a data science MS program that is any different from a MS in statistics. I would look very carefully at what the requirements of either program cover, see if internship opportunities are available, etc.
 
  • #5
Any Statistics program worth it's salt will require their students to program. While it may not be advance programming, the truth is one doesn't need to know many advance concepts in computer science for statistical programming. I think StatGuy concerns are well laid out. In my experience, Data Science MS from even well known schools leave a lot to be desired. I think they make exceptional Business analyst or traditional BI people, but with regards to what I consider Data Science, there isn't enough sufficient mathematics in those programs to leave me feeling confident in their ability to interpret the intercept of a regression slope properly.
 

Related to Masters in Statistics vs in data science? Is DS just buzz?

1. What is the difference between a Masters in Statistics and a Masters in Data Science?

A Masters in Statistics typically focuses on the mathematical and theoretical foundations of data analysis, while a Masters in Data Science combines statistical analysis with computer science and programming skills to extract insights from large datasets.

2. Which degree is more suitable for a career in data analysis?

It depends on your career goals and interests. If you are more interested in the mathematical and statistical aspect of data analysis, a Masters in Statistics may be a better fit. If you want to work with big data and have strong programming skills, a Masters in Data Science may be a better choice.

3. Is Data Science just a buzzword?

No, data science is a rapidly growing and important field in the age of big data. It involves using various techniques, such as machine learning and data mining, to extract insights and make predictions from large datasets. Many industries, including healthcare, finance, and marketing, rely on data science to make informed decisions.

4. Can I pursue a career in data science with a Masters in Statistics?

Yes, a Masters in Statistics can provide a strong foundation for a career in data science. However, it may be beneficial to supplement your statistical knowledge with programming skills and courses in data science topics such as machine learning and data visualization.

5. Are there any overlapping courses between a Masters in Statistics and a Masters in Data Science?

Yes, there may be some overlapping courses such as introductory statistics, linear regression, and experimental design. However, a Masters in Data Science may also include courses in computer science, data mining, and data visualization that are not typically covered in a Masters in Statistics program.

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