Hey,
I’m taking five classes next semester (15 credits) but four of them are likely more difficult than anything I’ve seen so far. I was wondering if anyone has taken a schedule like this and can comment on how realistic it is. Here’s the schedule:
Intro to Real Analysis 1
Linear Algebra 2 (proof based)
Probability Theory (calc based and proofy - not measure theoretic)
Statistics for Scientists and Engineers
Discrete Structures (basically math for computer scientists. Not too worried about this one.)
I haven’t taken any stats before, so that kinda worries me. I have however taken a proof-writing course (pre-req for real analysis), the standard (honors) calc 1-4 classes and Linear Algebra 1 (all As). This semester I’m in 19 credits and am doing well, but the classes aren’t as high caliber as next semester. What do you guys think?
I think you’re very dedicated and a lot better disciplined than me with 19 credits this semester and you’re planning to take that haha.
To be helpful though, statistics won’t be too hard compared to the top three, I think that much math is going to be a headache. You’re going to be spending a lot of time studying the top three, but if you managed 19 credits, it’s possible.
Discrete Structures - This should not be challenging.
Statistics for Scientists and Engineers - Doubtful.
Probability Theory - Could be a bear of a workload, just depends on who is teaching.
Linear Algebra 2 - I don’t think I can comment on this as I never had to take Linear Algebra 2. Linear Algebra “1” was proof-based for me. Looking back, at the time it was somewhat difficult. Since I’ve graduated with a math degree, it wasn’t that bad.
Intro to Real Analysis - I’d be careful with this one. This can eat up A LOT of your time. Depending on how smart/quick you are, of course.
Overall: I’d probably drop a class if it’s not necessary for your degree. I had taken a ton of statistics classes and “statistics for scientists and engineers” was something I considered taking (was interested in going into engineering, still am as I am applying to grad school now), but I did not ultimately do it. It would’ve been an easy A and review for me.
If you work - don’t take this much.
If you don’t work and want to take this much, be prepared to put in the time. It could be a real time sink. This will impact your life in a negative way if you’re not too careful. I had to force myself through my departments hardest classes to graduate on time. It was not fun and I did not have much of a life outside of the library. It was worth it to graduate.
If you don’t work and don’t want to take this much, find a way to re-schedule some of your classes.
It just really depends on you. How confident are you?
I also don’t find the intro to proofs class indicative of how you will do in Real Analysis.
Thanks for the thoughtful reply. I’m pretty confident that I could pass this course load, but not as confident that I can maintain my GPA (3.9+) through it. Of course I expect to take somewhat of a hit to my grades as I move to harder courses, but I would like to minimize this as much as possible. I am working this semester (as a tutor), but don’t intend to work next semester unless I can get involved with research.
I’ve heard horror stories about real analysis, but will definitely be taking it as it’s a requirement for my degree. In terms of potential changes to the schedule, I could drop discrete structures or swap an easier class for probability theory.
That being said, is there any advice you could offer on how to prepare for real analysis? I’m not sure which text we’ll be using (the professor who usually teaches it at my school is retiring), but do you think picking up a gentle introductory text and working on it over the summer would help? I know real analysis is an important subject, so I want to have a good first experience with it.
I’ve taken schedules like this and all of those classes in the past. How realistic it is depends on how hard you are prepared to work and how much mastery your school expects. With 5 math courses, I’d add a non-math course for a little variety and work through some of the textbooks during the summer. I particularly like Rudin or Royden (more advanced) for introductory analysis and Sheldon Ross for calculus based probability. Consider looking for a very touchy feely or intuitive and descriptive book on stats to read before the course, so that you can see the forest through the trees during that course.