Applied Maths Puns

A bit of a emotional talk rather than talking about theory. I never thought I would end up studying maths. I started uni in summer last year and there I met Real Analysis, and boy... just proofing things in general, I feel like I'm so bad at it, or at least not as good as I should be.

The worst part is I could technically graduate while being bad at Real Analysis, but it feels wrong: how could I call myself a mathematician if I struggle with the area of math that embodies proofing and the showing the "truth" of a statement? How could I call myself a mathematician if I struggle so much with the rigorousness? Not a little, but a lot.

I love the rigorousness because it makes me feel stable. Imagine the great things humans have been able to do just because 1+1 is always equal to 2. It's not up to God's attitude today, if he wakes up with the left foot and says "Today, I wanna make it so 1+1=3. *poof* Done!" No. 1+1 always equals 2. Always. And it's because of this "always" that we've came to construct great, useful and still rigorous ideas over 1+1=2.

But me struggling to what is probably the essence of math, at least in my eyes, makes me feel dirty. For context, maybe I want to pursue a carrer in quantitative finance, which means learning stochastic calculus, which seems an awesome branch from the little I've seem so far, but requires also having a good ability to proof things.

Even if someone with more experience in the field tells me that not that much mastery in proofing is necessary, I still feel like a fraud if I never get satisfied with my ability to proof things.

Finally, I feel like, to cope with this situation, I'm starting to value the usefulness of math over its rigorousness.

Ok, maybe to spark discussion: in your stage in life now, do you feel satisfied with your ability to proof things? If you consider yourself not good at proofing rigorously stuff, does it bother you or it isn't important to you? I'm just a naive math student wanting to explore others' perspectives. Thanks for your time. :)

So I’m going to be graduating at the end of this semester, and I’m having a lot of trouble finding a job. I’m majoring in applied math, and looking at the first destination survey it seems like most applied math majors go in one of three directions: graduate school, software engineering or data science type roles, or finance related positions such as actuaries and financial analysts. I have no interest in going to graduate school, and I never got into coding (believe me, if I could go back and start over I would probably be a computer science major). So this pretty much leaves me with the last option. However, I don’t know enough accounting or whatever to make it through the interviews for finance jobs. I’ve already done some, and let’s just say they did not go well.

TLDR: What other jobs can you get as an applied math major? I feel like all of the time and money I have spent on college has been for nothing because I still can’t find a job.

Also, some advice for anyone at the beginning of their college career: make sure you have an idea of what job you want to do before you decide on a major. Doing it after the fact is no fun.

I’ve been looking into graduate programs and have realized that I’d want to do something with both applied math and statistics (eg: stochastic PDEs). So far, CU Boulder seems to be the only program I could find whose applied math PhD program covers statistics significantly (it’s essentially a hybrid of a stats and applied math phd). I’m wondering if there are any other decent programs like that.

P.s. I’m also considering a “PhD minor” as a backup option, since several schools do that, but that just sounds like extra work so it’d rather find other programs like CU Boulder first.

Just a heads up for anyone who’s going into this course. The course site is up and when you go to site info the site admin is none other than James Uren. It’s like my mental health can’t ever catch a break. Anyways I wish you all luck troopers, we survived WW1 now it’s time to get drafted to fight WW2.

Looking for help on what classes to take and what teachers to avoid. Anyone here in either of those majors who’d be willing to help a sophomore?

At the beginning of my math career, I overhead a Ph.D. student talking about how they were using linear algebra/vectors in a research project related to space. I did not have the chance to go up to them. I also heard that in higher levels of linear algebra, you might have to calculate or prove things such as if "we have 30 vectors in a 3D space, where do they intersect?" When do scenarios like these, such as figuring out the intersection of vectors, come up outside of pure math? It sounds like things like this would apply to physics/astrophysics.

I'm asking because I love math and physics, but I do not think I want to focus on pure math as a career; however, I would love something that includes a lot of math, such as theoretical physics. I wonder if linear algebra is used heavily in any of these fields

I was thinking probability theory, theory of stats, regression theory, and bayesian analysis/big data. I was also considering applied linear algebra. However, I took all of these classes in undergrad (I was a CS and math/stats major) at the undergraduate level. So I’m wondering if retaking them at the graduate level would be somewhat redundant and if I should take other classes instead. If so, what else could I take?

I wanna do a PhD and then one of the careers that I’m aiming for is in quant finance research. However, I’m not sure as to which subject I should pursue a PhD in. Statistics appears to be the most common one on LinkedIn at top firms and hedge funds, however, my concern is that then my skillset would be limited to statistical modeling.

Operations Research sounds like the one thats most directly applicable, but there’s limited programs for it, plus it sounds too specific in its focus and (oddly enough) too broad in the topics it covers.

Applied math sounds like the hardest, but I could learn all three: optimization and probabilistic/statistical and numerical/mathematical modeling. But perhaps its a bit excessive?

I’d appreciate any input!

I'm a high school student and I wrote a paper about a working method for modeling one-dimensional heat transfer into an egg. It is an applied math paper, and the most complex thing I have done is deploy parametric equations and some simple multivariate calculus.

Despite using relatively simple math, I feel that my work answered a question that has been largely ignored by the literature on this topic, which is accurately modeling the surface area of an egg. I worked on this as a passion project, but I feel that maybe it's worth publishing. At the same time, I feel like anyone who is experienced in mathematics would scoff at its lack of complexity and immediately dismiss it as amateurish. Should I still submit my paper to my regional journal?

Hi, I'm an incoming freshman for Spring 2022, and I'm majoring in mathematics.

How can I double major in applied math with stat&data science?

Also, is there another better option for math instead of applied math for studying a double major?

It's been a year since I took math 221 so I don't remember a whole lot from the course. Anyone who took 307 got any suggestions on how to prepare for it over the break?

guys i need serious help..i just wanna pass and not to sound bad but i wish i had someone in my position for support〒▽〒.idk if i can pass itself......iv tried studieing thi subject somany times but when there are no proper resources,it SUCKS

I just saw an acceptance post on gradcafe......

I was fairly certain on pursuing a degree in computer science until I recently learned of Operations Research (OR). The core theme of OR seems to aggregate and bring clarity to many scattered interests I've accrued over the years but have never been able to put into words. All of a sudden, I'm not as certain about computer science and have been looking into master's in Operations Research, Applied Math, as well as a few unique programs in Algorithms, Combinatorics, and Optimization (ACO).

I would just go ahead and pursue a comprehensive masters in OR/applied math, however, there are a few hang ups:

1. As much as I know that it's not everything, I value employability and I know that I will be able to get a job fairly easily with a CS degree.
2. I have a minor in CS, so getting into a graduate program will not be difficult. I meet all of the prereqs for most CS masters programs and am already in the process of applying for a few. By contrast, I do not have that many math classes under my belt. I will be graduating in a couple of months and have only taken stats, discrete math, and linear algebra. I have gotten mediocre grades in these classes and I assume most applied math grad programs require that applicants have stronger math background.
3. There is already significant overlap between OR/applied math and CS. I think I would be able to do good work in the OR field as someone with training in algorithm development, etc.

Essentially, I am in dilemma and would greatly appreciate any advice as to which program I should apply to (CS or OR/applied math). Thank you!

tl;dr - I enjoy making and applying models and algorithms to gain insights and make better decisions across multiple domains. I have a minor in CS. Should I apply for a MS in CS or MS in applied math/operations research.

I think I am interested in applied math. Right now, I am a math and physics major. I love math and the challenge proofs, especially linear algebra, and I understand why many want to pursue pure math. Still, I am currently more interested in doing math with a specific purpose in mind rather than a pure development in math itself. I am early in my career, but I would love to hear some examples of exciting developments in applied math. For instance, I know from my book that Gauss used math to rediscover an asteroid (but maybe that was more of a physics development?) and used math to calculate things like the orbit of planets. Again, perhaps this is more physics and less applied math. I know theoretical computer science is a big field, and while I am not interested in computers, if there is a paper in TCS that you found fascinating and would like to share, I'd be happy to hear anything.

TL;DR: I am curious what the most exciting developments in applied math have been because I am trying to grasp better what applied math is. The last time I asked, my professor told me it's coming up with testable algorithms, but it is hard to wrap my head around how this works as someone only a few years into math.

edit: sorry for not replying to anyone yet; I had midterms and got caught up :)

Hello everyone, I am currently in community college and I just wanted to know which UCs (University of California) have the best Applied Math or Math programs. There are some UCs that have guaranteed admission which is why I want to know because I can only choose 1.

If someone could kindly rank them that would be nice!

Hi everyone!

Prospective UNSW student here, im considering doing science/ math and might major in either stats or applied math.

It would really help if I could get to know a thing or two about these majors before i finalise my uac preference

Are the courses well structured/ well taught? (would harder math courses feel a bit rushed due to the trimester system?) Is the cohort competitive? Just how hard is the math? Is it difficult to get a scholarship? and would you recommend the major?

anything relevant would be helpful, thanks!

If so, how was it and would you recommend? I’m going to uni next year, into the applied maths major but I have my options open for statistics and data science.

Geo experts, I'm a math student doing Fourier analysis projects. I need to make tide predictions using Fourier analysis/series. Where can I download real tide data (water level) for a few continuous months? Any sea station would be fine.

I searched for many hours, but can't find where to download the data (such as csv).

The best site I found is below. But only provide 1-hour data.

https://psmsl.org/cme/downloaddata.php

Thank you a lot for any help.

I am looking for masters programs in computational and applied mathematics that allows students to specialize in or take extensive electives in computer science (preferably the former).

Is anyone here familiar with or an alum of such program? Any info would be greatly appreciated!

Not exactly engineering but close/relevant enough. I cant decide between a graduate program in applied math, operations research, and statistics. I know they’re all similar and have a lot of overlap, but I’m not sure which to choose.

Here’s what I wanna do: something with developing probabilistic and statistical models, not just something that’s entirely data driven but also has a numerical and analytical component to it. I suppose the best example would be stochastic partial differential equations (which I’ve seen most often in operations research and then applied math departments). Some fields that interest me are quantitative finance research, data science, and business analytics/optimization.

I understand that statistics might be the most marketable and directly employable program, but I don’t wanna be restricted to just data analysis when building models. Perhaps my perception of what a statistician can do is flawed? I’d appreciate any input.

I have to choose between Nicolas and Shimozono

Hi Everybody!

I was just admitted to Yale SCEA, and I've been doing a bunch of research on the course catalog and my prospective major at the moment: applied mathematics. However, I haven't been able to find much info about the major outside of the yale website. Would anybody let me know what their experience has been with this major - or other related ones like engineering - and whether they have any advice for an incoming first year? Or just any experience with the math department:) Thanks so much!!

edit: made question more general

Hello, I'm a physics undergrad who is not interested in research anymore and would rather use math skills to make money. Is a degree in Applied Math a bad idea? I was wondering if this would be useful maybe in the finance or tech industry, and if I could one day move up to a manager position? Thanks.

It's easier for me to work with things with visual components rather than just pages of text in case that influences anyone's answer. Thanks for any help

hi, does anyone have any idea what topics we're supposed to take for both of these subjects? and it would greatly be appreciated if you could provide references to study. tia :>>

Hello, I am considering doing a PhD in applied math, though in the very early planning phases of this endeavour.

I’ve been out of academia for a couple years now, and I doubt my letter writers could remember me, so the JHU Part time online program is especially attractive to me, as it requires no letters of recommendations, able to work around my work schedule, and my employer is willing to pay for credits on my behalf. I believe from my undergraduate credits, I have enough math to be admitted.

That all said, would it be remotely possible for me to end up in an applied math or statistics PhD program after this MSE? It appears most of these courses are taught by adjuncts, but there is a thesis option where I would find a faculty advisor.

Are there other programs out there that may serve as a stepping stone for a PhD in applied math? My particular interests are in stochastic processes and systems.

So I’m struggling in math and it’s the second day of the new quadmester. Math has always been a foreign language to me, I also can’t understand how people think it’s fun. So how will this effect my post secondary education opportunity’s. I don’t really know what I wanna do when I’m older, but it’s definitely gonna be hands on and not a fucking office job. Can I still go to Uni or no

Does anyone have any good recommendations for books on applied linear models/regression that would be acessible to undergrads with minimal math backgrounds? I'm talking students who have taken some type of intro stats course but might not even have much mastery of calculus, let alone matrix algebra. I've seen some books that technically don't require calculus, but still have complicated algebraic derivations that I think many students would struggle with due to a general lack of mathematical maturity. I expect many will still be largely in the high school mindset that math/stats means you plug numbers into formulas and compute other numbers.

I'm looking for something that can get at the concepts and applications of linear models and start pushing students to transition to a more mature mindset about statistics but doesn't totally throw them into the deep end right off the bat.

Thanks in advance!

SCEA Yale (Applied Math), EA UMich, GIT, UT Austin, UIUC (CS)

Character customization menu: Asian male middle class bay area no legacies (dad did one year at a state uni) no hooks

UW 4.0 SAT 1580 school doesn't do weighted but i chose all 'hardest' courses

trevor packer paychecks: Phys 1, Phys C, Lang, CSA, CSP, Calc BC, Chinese (5s), Euro History (3 loll)

perfect score on AP CSP (top 0.2%) but I'm not sure if that matters

Awardos: USAMO, AIME 4x, Mathleague Nationals <10th place, shit ton of AMC distinctions and other math contests, random local coding awards, Top 0.5% of NAV's listeners on spotify

Out of curriculars

Math (4 years): study for math competitions weekly, read journals and websites, visit college profs lectures, compete on a team for SMT and ARML and others, travelled cross-state to attend contest. no room for this so it went in additional info

class vp (2 years): manage budget in the thousands $, spirit week, fundraisers, all that jazz

coding: just shit I do for fun basically. Made a few userscripts for a mf .io game (one of them got 10,000 downloads), a few shitty websites, working on niche environment conservation app, nothing "successful" though

Math club, officer for 4 years and vp now

summer volunteering (3 years) collaborated with schools in rural [home country] recovering from earthquake. contacted schools, created curriculum, organized large-scale games and debates. Absolutely love it, taught them how to water bottle flip! Will be going back and expanding the program even after graduation

Paid job teaching at local afterschool, volunteer as tutor. Both for math

chess: play for fun online lol, rated ~1500, chess .com's engine called one of my moves brilliant and I instantly blew a load

JV Swim team (1.5 years) I stun my competition with my deity-like physique

CS club officer, present on algorithms

Summer program on IoT: created model for fitbit data processing. It was basically pay-to-get-in and I didnt like it so I didnt include in EC's, only mentioned briefly in some supps

LoR's

Math teacher: I'm her TA and we're close and she knows I'm smart&motivated and loves me and definitely most likely doesnt find me annoying hopefully lol! writing this in her class rn

Econ teacher: had him before, not too close but he writes good letters full of praise, i sent him an email on what to write about

Counsellor: I've engaged in 5 email battles and meetings with her about skipping a class requirement, community colleg

They both seem to have mixed reviews, and I’m indecisive about who to take. Has anyone had these professors before? I’d say I have good study habits and I’m passionate about mathematics so I would say I’m not too worried about the course itself.

I cant decide between a graduate program in applied math, operations research, and statistics. I know they’re all similar and have a lot of overlap, but I’m not sure which to choose.

Here’s what I wanna do: something with developing probabilistic and statistical models, not just something that’s entirely data driven but also has a numerical and analytical component to it. I suppose the best example would be stochastic partial differential equations (which I’ve seen most often in operations research and then applied math departments). Some fields that interest me are quantitative finance research, data science, and business analytics/optimization.

I understand that statistics might be the most marketable and directly employable program, but I don’t wanna be restricted to just data analysis when building models. Perhaps my perception of what a statistician can do is flawed? I’d appreciate any input.

I was thinking probability theory, theory of stats, regression theory, and bayesian analysis/big data. I was also considering applied linear algebra. However, I took all of these classes in undergrad (I was a CS and math/stats major) at the undergraduate level. So I’m wondering if retaking them at the graduate level would be somewhat redundant and if I should take other classes instead. If so, what else could I take?

I was fairly certain on pursuing a degree in computer science until I recently learned of Operations Research (OR). The core theme of OR seems to aggregate and bring clarity to many scattered interests I've accrued over the years but have never been able to put into words. All of a sudden, I'm not as certain about computer science and have been looking into master's in Operations Research, Applied Math, as well as a few unique programs in Algorithms, Combinatorics, and Optimization (ACO).

I would just go ahead and pursue a comprehensive masters in OR/applied math, however, there are a few hang ups:

1. As much as I know that it's not everything, I value employability and I know that I will be able to get a job fairly easily with a CS degree.
2. I have a minor in CS, so getting into a graduate program will not be difficult. I meet all of the prereqs for most CS masters programs and am already in the process of applying for a few. By contrast, I do not have that many math classes under my belt. I will be graduating in a couple of months and have only taken stats, discrete math, and linear algebra. I have gotten mediocre grades in these classes and I assume most applied math grad programs require that applicants have stronger math background.
3. There is already significant overlap between OR/applied math and CS. I think I would be able to do good work in the OR field as someone with training in algorithm development, etc.

Essentially, I am in dilemma and would greatly appreciate any advice as to which program I should apply to (CS or OR/applied math). Thank you!

tl;dr - I enjoy making and applying models and algorithms to gain insights and make better decisions across multiple domains. I have a minor in CS. Should I apply for a MS in CS or MS in applied math/operations research.

I was fairly certain on pursuing a degree in computer science until I recently learned of Operations Research (OR). The core theme of OR seems to aggregate and bring clarity to many scattered interests I've accrued over the years but have never been able to put into words. All of a sudden, I'm not as certain about computer science and have been looking into master's in Operations Research, Applied Math, as well as a few unique programs in Algorithms, Combinatorics, and Optimization (ACO).

I would just go ahead and pursue a comprehensive masters in OR/applied math, however, there are a few hang ups:

1. As much as I know that it's not everything, I value employability and I know that I will be able to get a job fairly easily with a CS degree.
2. I have a minor in CS, so getting into a graduate program will not be difficult. I meet all of the prereqs for most CS masters programs and am already in the process of applying for a few. By contrast, I do not have that many math classes under my belt. I will be graduating in a couple of months and have only taken stats, discrete math, and linear algebra. I have gotten mediocre grades in these classes and I assume most applied math grad programs require that applicants have stronger math background.
3. There is already significant overlap between OR/applied math and CS. I think I would be able to do good work in the OR field as someone with training in algorithm development, etc.

Essentially, I am in dilemma and would greatly appreciate any advice as to which program I should apply to (CS or OR/applied math). Thank you!

tl;dr - I enjoy making and applying models and algorithms to gain insights and make better decisions across multiple domains. I have a minor in CS. Should I apply for a MS in CS or MS in applied math/operations research.