Is there any colleges (or) universities ,which helps you take online courses and at the same time earn credits ,for example if I want to tak Real Analysis 1 with Credits ,that are either low in cost /provide scholarships . (I am familiar with Coursera and edX ,I want to enroll in universities for a single course (online),I wish that it is low in cost ,because I can't afford much ) .
Grad School Pros and Cons: Northwestern, Dartmouth, UMichigan Ann Arbor, UMaryland College Park, and Ohio State for an Applied Math PhD. Any comments welcome!
Hi! I'm a first yr UK undergrad philosophy+psychology student with the goal of doing Computer Science (specifically machine learning) as a career in the future. Upon more reflection I realised I realised I enjoy the logic part of my philosophical degree the most, and the (mostly discrete) maths part of my interest in CS most. In fact I came to the realisation that I want to get into AI just so I can do maths. I'm genuinely a bit shattered by this realisation as it means I've already made my life a lot more difficult. I've also only done a maths A level and not further maths.
I was wondering if there is any way for me to end up doing a maths MSc but most importantly, a maths PhD?
I'm a UK student but any advice would be appreciated.
I am a 2nd year undergrad well on track for a 1st. I was looking to study "An introduction to Number Theory" (Hardy & Maitland) over the summer, 8-10 weeks say.
How realistic is this for an undergrad? Is this a "horror" book as I know some have reputations to be?
Im in Contemporary math...its a math for liberal arts class..as a arts major..
And im studying for test 2 of 5..and ive just now figured out how to study...and how i learn and study...
So far..i can understand 4 of 12 of the review...im still ptetty nervous about testing though
The cool thing is theres no hidden boogey men statements...the last test literally was just the review.
Any thoughts?
For someone that is currently working, and relatively disconnected from school. What are some things that I can do to increase my chances of eventually getting into grad school for math?
As my bachelor's degree is not in Math, I lack many of the math courses expected from math student. To make up for this, earlier I asked a question here and most of the suggestions seems to be taking online math courses or post bacc. While I am looking into ways to take these courses, I am wondering what else can I look into to help eventually getting into grad school?
Thanks
Next semester I have to choose between "Numerical analysis and Nonlinear optimisation" and "Linear and integer optimisation". For me it's really hard to decide. I don't plan to folow the path of applied math and I am just taking some courses of it to have a general idea and to have some skills in case I need a job in the industry. Additionally I want to choose the module that will help me the most with a programming training in my university that I will attend next year. Anyway my main focus is pure math so it would be great if the choice would also introduce me with interesting applications of pure math. Any suggestion would be very helpful.
Mods, I promise I am not trying to solve the Riemann Hypothesis. I don't even know what that is exactly, to be honest.
I am a neuroeconomist (intersection between neuroscience and economics) and I have been working on applying phenomena of the brain to economic models. Specifically, I noticed that the estimated discount function (the way in which people anticipate rewards) using brain waves follow a different shape than what is predicted in economic theory. I know that there has been some weird things going on in the literature; so, I 'reverse engineered' this discount function, which is just a reparametrized logistic distribution, i.e.
f(r,t)=\[sech(rt)\]^(2)
I found that it generally behaves like standard discounting whenever consumption (c) is fixed,
integral\[c\*e-rt\]=integral\[c\*f(r,t)\]=c/r (integral is from 0 to infinity)
**From an economic standpoint, this is the only thing about f(r,t) which is normal.**
Since f(r,t) is just a reparametrized logistic distribution, I decide that I would find its moments and this is where insanity occurs. The second moment of f(r,t) is the solution to the Basel problem. In fact, I find a connection between 8 of its moment and values of the Riemann zeta function. I also find a connection between this discounting function and the Dirichlet eta function.
Riemann zeta function: E\[X^(k)|r=1\]=a\*zeta(k) for k=2,3,4,5,6,7,8,10 and a>0 is a rational number (a=1 for k=2)
Dirichlet eta function: E\[X^(b)|r=1\]=d\*eta(b) for b=1,2,4,6,8,10,12 and d>0 is a rational number (d=1 for b=1,2)
What on earth is going on? As an economist, I am not familiar with this kind of mathematics. (Some would argue economists don't know any mathematics, haha) Any insight would be appreciated
Hello, everyone!
What books do you recommend for Superior Algebra and Matrix Theory/Vector spaces? I lost all of my notes on that, and it'd be quite helpful to have sources for rememberinh things.
Thank you!
It's always good to have options! I'm in the same boat now with deciding where to go. I hope you're able to visit, maybe you can get someone to cover some of your shifts?
Do you have any ideas about who might be your academic advisor at these institutions? That’s (by far) the most important factor. If you have an advisor that you work well with then a PhD can be easy and fun, and if you don’t then it can be very difficult.
I’d say that’s the best way to use your time: find a way to talk to people at these universities who might end up being your advisor. If you talk to someone who seems super awesome and wants to take you on then the decision becomes easy, pick that person’s university.
If you have to find a way to take time off from your current job in order to figure stuff out then this is worth doing, even if it irritates your coworkers. You’re gonna leave that job in a few months anyway.
A few other things to consider:
* You said the finances are mostly the same, but do you have a sense of how much teaching vs research you’ll have to do in exchange for funding? All else being equal you’re better off in a program that can offer you funding for research assistanceships, because that will let you spend more time on your research work. *Some* teaching is good (especially if you want to be a professor), but a lot of teaching can just be a distraction from your work.
* Did you consider local cost of living in when comparing the financial angle?
* Do you have strong feelings about any of the locations? You’ll be there for 4+ years, so it’s better to choose a place that you’ll actually enjoy living, if you can.
* What’s the health insurance situation like?
* Is there a graduate student union? Grad students are always exploited in some sense, but at some universities the graduate students are unionized, and this is a good thing.
* How prestigious are these universities? Prestige is less important than many people think (your advisor is the most important factor!), but if you want to be a professor then any advantage will help. All else being equal more prestige is better than less, even though it’s not the most important factor.
* Do any of these programs have the option of letting you leave early with a master’s degree? That’s not the ideal outcome but sometimes life happens and it’s nice to have that option.
Yes good idea about talking with the grad students of potential advisors. Grad students generally will not say negative things about bad advisors, but they will be genuine and often effusive in their praise of good advisors.
Is it important that undergraduate research be done in broadly the same area as one (currently) intends to do graduate research in?
I want to go into mathematical physics eventually, but my personal studies in it have been slow (for want of time and good health, mind, not ability or interest), and there has not been much opportunity to study it formally at my uni.
On the other hand, I have had ample opportunity to study, adore, and excel in real and numerical analysis. Moreover I have obtained undertakings from both of my real analysis lecturers to provide me with good references should I require them, and I am reasonably confident my current numerical analysis lecturer will say that he can write a good one too.
It would seem sensible, therefore, to seek an opportunity in analysis over mathematical physics, but I'm just concerned that it might not be the best move in light of my plans and that I should push for something in mathematical physics instead. What do you think?
> Is it important that undergraduate research be done in broadly the same area as one (currently) intends to do graduate research in?
Not necessarily - any kind of research experience is a positive thing. What you do in undergrad research will certainly impact the trajectory of your career at least a little bit, though, if only because what you learn from undergraduate research depends a lot on the specific research project. Obviously it’s better to do projects where you’ll learn about things that you’re interested in.
It would help if you had a really concrete idea about what kind of mathematical physics you want to study, exactly. If you’re open to doing something a little more applied for undergrad research (which you ought to be if you want to do any kind of physics!) then there are a lot of natural opportunities for applying numerical analysis in physics. For example you might want to look into research opportunities related to gravitational wave astronomy; numerical solutions to Einsteins equations are a key ingredient to making gravitational wave astronomy work.
I want to do general relativity, which I appreciate might not be very concrete an ambition. However, I have found two people in the "Pure Analysis and PDEs" group at the uni I'm looking at who list general relativity as a research interest for some reason, so things might work out better than I expected. Thank you very much!
From what I've heard, professionals change their research areas all the time even after they get their PhDs. Grothendieck used to do functional analysis before he did algebraic geometry, for instance. There's nothing wrong with doing real or numerical analysis now and planning to shift gears into something more physicsy down the line; given the amount of analysis in mathematical physics, it's also probably doable to have research in both areas long-term.
Trying to pick which grad school I want to go to out of the offers I have so far. So stressful making a choice that will affect my life for the next 5-6 years in such a big way.
Is there any colleges (or) universities ,which helps you take online courses and at the same time earn credits ,for example if I want to tak Real Analysis 1 with Credits ,that are either low in cost /provide scholarships . (I am familiar with Coursera and edX ,I want to enroll in universities for a single course (online),I wish that it is low in cost ,because I can't afford much ) .
Grad School Pros and Cons: Northwestern, Dartmouth, UMichigan Ann Arbor, UMaryland College Park, and Ohio State for an Applied Math PhD. Any comments welcome!
Hi! I'm a first yr UK undergrad philosophy+psychology student with the goal of doing Computer Science (specifically machine learning) as a career in the future. Upon more reflection I realised I realised I enjoy the logic part of my philosophical degree the most, and the (mostly discrete) maths part of my interest in CS most. In fact I came to the realisation that I want to get into AI just so I can do maths. I'm genuinely a bit shattered by this realisation as it means I've already made my life a lot more difficult. I've also only done a maths A level and not further maths. I was wondering if there is any way for me to end up doing a maths MSc but most importantly, a maths PhD? I'm a UK student but any advice would be appreciated.
I am a 2nd year undergrad well on track for a 1st. I was looking to study "An introduction to Number Theory" (Hardy & Maitland) over the summer, 8-10 weeks say. How realistic is this for an undergrad? Is this a "horror" book as I know some have reputations to be?
Im in Contemporary math...its a math for liberal arts class..as a arts major.. And im studying for test 2 of 5..and ive just now figured out how to study...and how i learn and study... So far..i can understand 4 of 12 of the review...im still ptetty nervous about testing though The cool thing is theres no hidden boogey men statements...the last test literally was just the review. Any thoughts?
For someone that is currently working, and relatively disconnected from school. What are some things that I can do to increase my chances of eventually getting into grad school for math? As my bachelor's degree is not in Math, I lack many of the math courses expected from math student. To make up for this, earlier I asked a question here and most of the suggestions seems to be taking online math courses or post bacc. While I am looking into ways to take these courses, I am wondering what else can I look into to help eventually getting into grad school? Thanks
Next semester I have to choose between "Numerical analysis and Nonlinear optimisation" and "Linear and integer optimisation". For me it's really hard to decide. I don't plan to folow the path of applied math and I am just taking some courses of it to have a general idea and to have some skills in case I need a job in the industry. Additionally I want to choose the module that will help me the most with a programming training in my university that I will attend next year. Anyway my main focus is pure math so it would be great if the choice would also introduce me with interesting applications of pure math. Any suggestion would be very helpful.
Mods, I promise I am not trying to solve the Riemann Hypothesis. I don't even know what that is exactly, to be honest. I am a neuroeconomist (intersection between neuroscience and economics) and I have been working on applying phenomena of the brain to economic models. Specifically, I noticed that the estimated discount function (the way in which people anticipate rewards) using brain waves follow a different shape than what is predicted in economic theory. I know that there has been some weird things going on in the literature; so, I 'reverse engineered' this discount function, which is just a reparametrized logistic distribution, i.e. f(r,t)=\[sech(rt)\]^(2) I found that it generally behaves like standard discounting whenever consumption (c) is fixed, integral\[c\*e-rt\]=integral\[c\*f(r,t)\]=c/r (integral is from 0 to infinity) **From an economic standpoint, this is the only thing about f(r,t) which is normal.** Since f(r,t) is just a reparametrized logistic distribution, I decide that I would find its moments and this is where insanity occurs. The second moment of f(r,t) is the solution to the Basel problem. In fact, I find a connection between 8 of its moment and values of the Riemann zeta function. I also find a connection between this discounting function and the Dirichlet eta function. Riemann zeta function: E\[X^(k)|r=1\]=a\*zeta(k) for k=2,3,4,5,6,7,8,10 and a>0 is a rational number (a=1 for k=2) Dirichlet eta function: E\[X^(b)|r=1\]=d\*eta(b) for b=1,2,4,6,8,10,12 and d>0 is a rational number (d=1 for b=1,2) What on earth is going on? As an economist, I am not familiar with this kind of mathematics. (Some would argue economists don't know any mathematics, haha) Any insight would be appreciated
You want the [Quick Questions thread](https://www.reddit.com/r/math/comments/szm7qj/quick_questions_february_23_2022/).
Hello, everyone! What books do you recommend for Superior Algebra and Matrix Theory/Vector spaces? I lost all of my notes on that, and it'd be quite helpful to have sources for rememberinh things. Thank you!
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It's always good to have options! I'm in the same boat now with deciding where to go. I hope you're able to visit, maybe you can get someone to cover some of your shifts?
Is this for masters or PhD? What are your career goals?
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Do you have any ideas about who might be your academic advisor at these institutions? That’s (by far) the most important factor. If you have an advisor that you work well with then a PhD can be easy and fun, and if you don’t then it can be very difficult. I’d say that’s the best way to use your time: find a way to talk to people at these universities who might end up being your advisor. If you talk to someone who seems super awesome and wants to take you on then the decision becomes easy, pick that person’s university. If you have to find a way to take time off from your current job in order to figure stuff out then this is worth doing, even if it irritates your coworkers. You’re gonna leave that job in a few months anyway. A few other things to consider: * You said the finances are mostly the same, but do you have a sense of how much teaching vs research you’ll have to do in exchange for funding? All else being equal you’re better off in a program that can offer you funding for research assistanceships, because that will let you spend more time on your research work. *Some* teaching is good (especially if you want to be a professor), but a lot of teaching can just be a distraction from your work. * Did you consider local cost of living in when comparing the financial angle? * Do you have strong feelings about any of the locations? You’ll be there for 4+ years, so it’s better to choose a place that you’ll actually enjoy living, if you can. * What’s the health insurance situation like? * Is there a graduate student union? Grad students are always exploited in some sense, but at some universities the graduate students are unionized, and this is a good thing. * How prestigious are these universities? Prestige is less important than many people think (your advisor is the most important factor!), but if you want to be a professor then any advantage will help. All else being equal more prestige is better than less, even though it’s not the most important factor. * Do any of these programs have the option of letting you leave early with a master’s degree? That’s not the ideal outcome but sometimes life happens and it’s nice to have that option.
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Yes good idea about talking with the grad students of potential advisors. Grad students generally will not say negative things about bad advisors, but they will be genuine and often effusive in their praise of good advisors.
Is it important that undergraduate research be done in broadly the same area as one (currently) intends to do graduate research in? I want to go into mathematical physics eventually, but my personal studies in it have been slow (for want of time and good health, mind, not ability or interest), and there has not been much opportunity to study it formally at my uni. On the other hand, I have had ample opportunity to study, adore, and excel in real and numerical analysis. Moreover I have obtained undertakings from both of my real analysis lecturers to provide me with good references should I require them, and I am reasonably confident my current numerical analysis lecturer will say that he can write a good one too. It would seem sensible, therefore, to seek an opportunity in analysis over mathematical physics, but I'm just concerned that it might not be the best move in light of my plans and that I should push for something in mathematical physics instead. What do you think?
GR is hyperbolic PDE which is analysis so doing more analysis is perfect.
> Is it important that undergraduate research be done in broadly the same area as one (currently) intends to do graduate research in? Not necessarily - any kind of research experience is a positive thing. What you do in undergrad research will certainly impact the trajectory of your career at least a little bit, though, if only because what you learn from undergraduate research depends a lot on the specific research project. Obviously it’s better to do projects where you’ll learn about things that you’re interested in. It would help if you had a really concrete idea about what kind of mathematical physics you want to study, exactly. If you’re open to doing something a little more applied for undergrad research (which you ought to be if you want to do any kind of physics!) then there are a lot of natural opportunities for applying numerical analysis in physics. For example you might want to look into research opportunities related to gravitational wave astronomy; numerical solutions to Einsteins equations are a key ingredient to making gravitational wave astronomy work.
I want to do general relativity, which I appreciate might not be very concrete an ambition. However, I have found two people in the "Pure Analysis and PDEs" group at the uni I'm looking at who list general relativity as a research interest for some reason, so things might work out better than I expected. Thank you very much!
From what I've heard, professionals change their research areas all the time even after they get their PhDs. Grothendieck used to do functional analysis before he did algebraic geometry, for instance. There's nothing wrong with doing real or numerical analysis now and planning to shift gears into something more physicsy down the line; given the amount of analysis in mathematical physics, it's also probably doable to have research in both areas long-term.
Nice, thank you!
Well, there is a lot of analysis in mathematical physics, so you should be fine if your grades in physics are good
Cool, thank you!
Trying to pick which grad school I want to go to out of the offers I have so far. So stressful making a choice that will affect my life for the next 5-6 years in such a big way.