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CS Math Double Major, Advice Please

  1. Feb 17, 2008 #1
    I was originally planning on being a CS major and a Math minor but after a little research, I found out that it's only about a semester more work to get a double major. Since I like Math and wanted to take more Math classes anyway, I'm going to get the double major. I'd like some suggestions on which math route to take. I plan on entering the work force as a computer scientist and I want to plan my math major to best suit that goal. I have two basic questions: Which math track should I choose (pure, applied, or statistics) and which electives do you recommend I take?

    My goal is to educate myself to become the best computer scientist I can be. If that means taking the hardest route to the double major or even if it means taking a couple additional classes beyond the requirement, then that is fine with me. Here's the details of the three track requirements:

    Mathematics Major/Minor Requirements
    Mathematics Major
    (College of Business, College of Liberal Studies, and College of Science and Allied Health)
    38 credits
    The following 7 courses are required:
    • 207 Calculus and Analytic Geometry I (5)
    • 208 Calculus II (4)
    • 225 Logic and Discrete Mathematics (4)
    • 309 Linear Algebra with Differential Equations (4)
    • 310 Calculus III: Multivariate Calculus (4)
    • 407 Real Analysis I (4)
    • 411 Abstract Algebra I (4)

    Also 9 additional credits chosen from:
    • 311 Number Theory (3)
    • 317 Graph Theory (3)+
    • 320 History of Mathematics (3)
    • 331 Intro. to Modern Geometry (3)
    • 341 Probability and Statistics (4)
    • 353 Differential Equations (3)
    • 371 Intro. to Numerical Methods (3)+
    • 408 Real Analysis II (3)
    • 410 Complex Analysis (3)
    • 412 Abstract Algebra II (3)
    • 413 Topics in Linear Algebra (3)
    • 441 Mathematical Statistics I (3)
    • 442 Mathematical Statistics II (3)
    • 461 Mathematical Physics (3)^
    • 480 Studies in Applied Mathematics (3)
    • C-S 453 Intro to Theory of Computation(3)+
    • PHY 470 Adv. Quantum Mechanics(4)



    Mathematics Major/Minor Requirements
    Mathematics Major with Applied Emphasis
    39 credits
    The following 7 courses are required:
    • 207 Calculus and Analytic Geometry I (5)
    • 208 Calculus II (4)
    • 225 Logic and Discrete Mathematics (4)
    • 309 Linear Algebra with Differential Equations (4)
    • 310 Calculus III: Multivariate Calculus (4)
    • 353 Differential Equations (3)
    • 371 Intro. To Numerical Methods (3)
    One of the following courses must be taken:
    • 461 Mathematical Physics (3)
    • 480 Studies in Applied Mathematics (3)

    Also 9 additional credits chosen from:
    • 341 Probability and Statistics (4)
    • 407 Real Analysis I (4)
    • 408 Real Analysis II (3)
    • 410 Complex Analysis (3)
    • 413 Topics in Linear Algebra (3)
    • 441 Mathematical Statistics I (3)
    • 442 Mathematical Statistics II (3)
    • 448 Operations Research (3)
    • 461 Mathematical Physics (3)
    • 480 Studies in Applied Mathematics (3)
    Three of the 9 additional credits may be met by completing one of the following courses:
    • CHM 310 Physical Chemistry Theory II (3)
    • C-S 453 Intro. To Theory of Computation (3)
    • PHY 470 Adv. Quantum Mechanics (4)
    • PHY 474 Adv. Computational Physics (4)


    Mathematics Major/Minor Requirements
    Mathematics Major with Emphasis in Statistics
    39 credits
    The following 10 courses are required:
    • 207 Calculus and Analytic Geometry I (5)*
    • 208 Calculus II (4)
    • 309 Linear Algebra with Differential Equations (4)
    • 310 Calculus III: Multivariate Calculus (4)
    • 341 Probability and Statistics (4)
    • 441 Mathematical Statistics I (3)
    • 442 Mathematical Statistics II (3)
    • 445 General Linear Models (3)
    • 446 Analysis of Variance and Design of Experiments

    Also 6 additional credits chosen from:
    • 305 Statistical Methods (3)
    • 371 Intro. to Numerical Methods (3)
    • 407 Real Analysis I (4)
    • 410 Complex Analysis (3)
    • 444 Introduction to Sampling (3)
    • 447 Nonparametric Statistics (3)
    • 448 Operations Research (3)
     
  2. jcsd
  3. Dec 16, 2009 #2
    Depends what kind of work you end up doing as a computer scientist. Statistics is a great route if you plan on going into data mining (think google and the like), where as applied math may be more practical if you plan on going the financial services route.

    As for electives:

    The stats route could be too much stats for data mining, so you can cram it into the Applied route by taking 341, 441 and 442. Linear algebra is also really important for a lot of the pattern recognition algorithms, so you may want to see what that course is all about.

    If you go the stats route, numerical methods is a good option 'cause it's all about approximating equations so they can be translated to algorithm form. Nonparametric stats is another useful course. (Don't know what your statistical methods course covers-if it's all applied stats using some software-take that.)
     
    Last edited: Dec 16, 2009
  4. Dec 16, 2009 #3
    I agree that numerical methods would be a good choice. When I took numerical analysis we covered things like the error involved in performing calculations with different data types, how to represent functions approximately for computation, how to solve various equations numerically, etc. I'm not sure what mathematical statistics entails, but we had a 2 semester series of advanced probability and advanced statistics based on multidimensional calc and set theory etc. Those would probably also be very relevant to any math-heavy coding you'd do in the real world.

    I use my probability course all the time at work. Every salaried employee in the company is actually required to earn a statistics (six sigma) certification, and the majority of mid/upper level people have to teach stats and mentor everyone else on their projects as their full time job for part of their career.
     
    Last edited: Dec 16, 2009
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