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

In summary: 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.In summary, based on your interests and level of study in statistics and computer science, you should be able to pursue either a combined major in mathematics and computer science or a combined major in statistics and computer science with no problems.
  • #1
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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 :)
 
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  • #2
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.
 
  • #3
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.
 
  • #4
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.
 
  • #5
Nous said:
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.
 
  • #6
Stephen Tashi said:
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.
 
  • #7
StatGuy2000 said:
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.
 
  • #8
homeomorphic said:
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.
 
  • #9
Nous said:
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?
 
  • #10
Nous said:
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.
 

1. What career opportunities are available with a combination of computer science and math?

The combination of computer science and math opens up a wide range of career opportunities, including data science, artificial intelligence, cybersecurity, financial analysis, and software engineering. These fields require strong analytical and problem-solving skills, which are developed through a combination of computer science and math.

2. How does combining computer science and statistics benefit a career in data science?

Data science relies heavily on both computer science and statistics. Computer science provides the programming and coding skills necessary to collect, clean, and analyze large data sets, while statistics provides the mathematical and analytical tools to interpret the data and draw meaningful insights. Combining these two fields allows for a more comprehensive understanding and application of data science.

3. Can a combination of computer science and math lead to a career in artificial intelligence?

Yes, a combination of computer science and math is essential for a career in artificial intelligence. Computer science provides the foundation for programming and building AI systems, while math, particularly linear algebra and calculus, is used to develop algorithms and models for machine learning and deep learning.

4. What skills will I develop by combining computer science and statistics?

Combining computer science and statistics will result in the development of strong analytical, problem-solving, and critical thinking skills. You will also gain proficiency in programming languages, data analysis, and statistical modeling, which are highly sought after skills in various industries.

5. How can a combination of computer science and math benefit a career in software engineering?

A combination of computer science and math is highly beneficial for a career in software engineering. Computer science provides the technical skills and knowledge to design, develop, and maintain software systems, while math provides the logical and analytical thinking skills necessary for problem-solving and optimization. Together, these fields will equip you with the necessary skills to excel in the field of software engineering.

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