Possibilities with Comp sci + math or comp sci + stats?

[Nous]

I am beginning a second undergraduate degree this fall and am trying to decide on a major but don't think I have enough information to discriminate between my top two choices.

My first degree was in mathematics education (where I developed a deep appreciation for math). I have interests in predictive analytics, "data science", AI, and mathematical and statistical modelling, among other things.

From these interests I have more or less narrowed my choice of major down to two:

1) combined major in mathematics and computer science

or

2) combined major in statistics and computer science

I have been trying to understand how my set of opportunities would differ depending on which of the two majors I choose.

Additionally, I am considering doing graduate studies and so I've been thinking it might be beneficial to go with option (1) math and compsci, and then do a MSc in statistics. However, if I am going to end up in stats anyway, might it be better to simply start there with option (2) for my undergrad?

I would be happy to provide clarification if any of this is too vague or broad :)

 

[homeomorphic]

I think you're probably good to go, either way. Do whatever you prefer. There's a lot of overlap between math and statistics. You might take real analysis and decide you don't like that stuff. That's what happens to a lot of people. I was the opposite and thrived on real analysis and pure math (until I had to write a dissertation, which popped my happy little math bubble and threw me into an existential crisis, but that's another story). Anyway, I don't think you have to decide right away. It would be pretty easy to switch from one to the other.

 

[homeomorphic]

I should say stats is more applicable/marketable towards what you are looking for. But with the computer science, I think you'll still be okay with a math major, and if not, you can always do the masters.

 

[StatGuy2000]

To the OP:

I would agree with what what homeomorphic stated earlier -- either degree option you pointed out will open doors to future graduate studies in statistics and/or career paths to data science or statistical modelling. Plenty of people I know have taken the path you are pursuing. I myself started out in pure math before pursuing graduate studies in statistics.

 

[Stephen Tashi]

I am beginning a second undergraduate degree this fall and am trying to decide on a major but don't think I have enough information to discriminate between my top two choices.

Do you have to declare a major immediately? How easy is to change your mind once you declare it?

From these interests I have more or less narrowed my choice of major down to two:

1) combined major in mathematics and computer science
or
2) combined major in statistics and computer science

I have been trying to understand how my set of opportunities would differ depending on which of the two majors I choose.

I don't know about opportunities. I suggest you first contemplate you intellectual compatibility with the subject matter. Let's assume mathematics of various kinds will be to your liking. Computer science or statistics may be a different matter.

How much statistics have you studied? For example, do you really like applying ANOVA to problems or do you find that dull? If you are interested in modeling (simulation), keep in mind that some statistics programs are weak in that topic.

What topics have you studied in computer science? Look at the text that's used for the algorithms course. See if the subject matter interests you.

 

[Nous]

Do you have to declare a major immediately? How easy is to change your mind once you declare it?

Unfortunately the second degree program at the University of British Columbia is fairly restrictive and there are limits on the number of attempted credits at each year level. I might be able to change programs after one semester but the window to so is small so I have been trying to front-load the research to before I declare my specialization.

How much statistics have you studied? For example, do you really like applying ANOVA to problems or do you find that dull? If you are interested in modeling (simulation), keep in mind that some statistics programs are weak in that topic.

What topics have you studied in computer science? Look at the text that's used for the algorithms course. See if the subject matter interests you.

I haven't studied statistics or computer science formally to any appreciable extent. However, my experience and self-study in each topic has been enjoyable, which is a good sign so far. I certainly enjoy diving deep into my subject matter and prefer a rigorous theoretical approach, but I evaluate theory with respect to the usefulness it might have in applications.

 

[Nous]

To the OP:

I would agree with what what homeomorphic stated earlier -- either degree option you pointed out will open doors to future graduate studies in statistics and/or career paths to data science or statistical modelling. Plenty of people I know have taken the path you are pursuing. I myself started out in pure math before pursuing graduate studies in statistics.

What was it like moving from mathematics to statistics? I have a fair bit of math experience under my belt but only two courses in statistics. I found those courses less challenging than some of my math courses.

I find that I need a relatively higher level of intellectual challenge to feel motivated (not too much of course!). Does statistics remain relatively easy or can it get challenging? I have heard that probability can be quite challenging.

 

[Nous]

I should say stats is more applicable/marketable towards what you are looking for. But with the computer science, I think you'll still be okay with a math major, and if not, you can always do the masters.

My intuition on this is similar. Statistics seems to be regarded as a relatively more employable or marketable major than mathematics in general, although I don't know the truth of this. Computer science also seems to possesses that "employable" attribution.

 

[StatGuy2000]

Unfortunately the second degree program at the University of British Columbia is fairly restrictive and there are limits on the number of attempted credits at each year level. I might be able to change programs after one semester but the window to so is small so I have been trying to front-load the research to before I declare my specialization.

I'm curious about this, but if you don't mind my asking, what was your original degree program? At the University of Toronto (my alma mater), second undergraduate degree programs in the Faculty of Arts and Science are only possible if both degrees are not Bsc or BA (for example, if you have earned a BA in a humanities or social science program, then the only second degree open to you is a Bsc in the sciences, including mathematics and statistics). In such a circumstance, there is a limited chance to transfer some of your courses taken to complete the second degree to fulfill any elective prerequisites. Is it similar with UBC?

 

[StatGuy2000]

What was it like moving from mathematics to statistics? I have a fair bit of math experience under my belt but only two courses in statistics. I found those courses less challenging than some of my math courses.

I find that I need a relatively higher level of intellectual challenge to feel motivated (not too much of course!). Does statistics remain relatively easy or can it get challenging? I have heard that probability can be quite challenging.

It really depends on the particular courses. I went from a straight pure math degree program to a joint specialist program (an equivalent to a double major) in math and statistics, in which I took all of the more challenging math courses and supplemented with statistics courses at the undergraduate level, and then proceeded to a Msc in statistics.

Some of the senior level undergraduate statistics courses (e.g mathematical statistics, theory of statistical inference, probability theory) were quite rigorous theoretically, much like senior level math courses, with emphasis on proofs and such. Other courses emphasize applications and these I've found easier for me. At the graduate level, each of the courses can be challenging in their own unique way. In some cases, like applied statistics, the challenge is in working with data and determining what steps one can take to solve the problems at hand, so things like exploratory analysis is quite important. Graduate level probability courses rely heavily on measure theory and real analysis, so I would expect that would provide the challenge you are looking for.