Best vector analysis mathematics books according to redditors

We found 79 Reddit comments discussing the best vector analysis mathematics books. We ranked the 21 resulting products by number of redditors who mentioned them. Here are the top 20.

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Top Reddit comments about Vector Analysis Mathematics:

u/nikofeyn · 13 pointsr/math

i have three categories of suggestions.

advanced calculus

these are essentially precursors to smooth manifold theory. you mention you have had calculus 3, but this is likely the modern multivariate calculus course.

  • advanced calculus: a differential forms approach by harold edwards

  • advanced calculus: a geometric view by james callahan

  • vector calculus, linear algebra, and differential forms: a unified approach by john hubbard

    out of these, if you were to choose one, i think the callahan book is probably your best bet to pull from. it is the most modern, in both approach and notation. it is a perfect setup for smooth manifolds (however, all of these books fit that bill). hubbard's book is very similar, but i don't particularly like its notation. however, it has some unique features and does attempt to unify the concepts, which is a nice approach. edwards book is just fantastic, albeit a bit nonstandard. at a minimum, i recommend reading the first three chapters and then the latter chapters and appendices, in particular chapter 8 on applications. the first three chapters cover the core material, where chapters 4-6 then go on to solidify the concepts presented in the first three chapters a bit more rigorously.

    smooth manifolds

  • an introduction to manifolds by loring tu

  • introduction to smooth manifolds by john m. lee

  • manifolds and differential geometry by jeffrey m. lee

  • first steps in differential geometry: riemannian, contact, sympletic by andrew mcinerney

    out of these books, i only have explicit experience with the first two. i learned the material in graduate school from john m. lee's book, which i later solidifed by reading tu's book. tu's book actually covers the same core material as lee's book, but what makes it more approachable is that it doesn't emphasize, and thus doesn't require a lot of background in, the topological aspects of manifolds. it also does a better job of showing examples and techniques, and is better written in general than john m. lee's book. although, john m. lee's book is rather good.

    so out of these, i would no doubt choose tu's book. i mention the latter two only to mention them because i know about them. i don't have any experience with them.

    conceptual books

    these books should be helpful as side notes to this material.

  • div, grad, curl are dead by william burke [pdf]

  • geometrical vectors by gabriel weinreich

  • about vectors by banesh hoffmann

    i highly recommend all of these because they're all rather short and easy reads. the first two get at the visual concepts and intuition behind vectors, covectors, etc. they are actually the only two out of all of these books (if i remember right) that even talk about and mention twisted forms.

    there are also a ton of books for physicists, applied differential geometry by william burke, gauge fields, knots and gravity by john baez and javier muniain (despite its title, it's very approachable), variational principles of mechanics by cornelius lanczos, etc. that would all help with understanding the intuition and applications of this material.

    conclusion

    if you're really wanting to get right to the smooth manifolds material, i would start with tu's book and then supplement as needed from the callahan and hubbard books to pick up things like the implicit and inverse function theorems. i highly recommend reading edwards' book regardless. if you're long-gaming it, then i'd probably start with callahan's book, then move to tu's book, all the while reading edwards' book. :)

    i have been out of graduate school for a few years now, leaving before finishing my ph.d. i am actually going back through callahan's book (didn't know about it at the time and/or it wasn't released) for fun and its solid expositions and approach. edwards' book remains one of my favorite books (not just math) to just pick up and read.
u/danns · 12 pointsr/Physics

Geometric algebra sounds extremely interesting. I definitely have heard that it makes a lot of vector calculus more intuitive, and apparently the results come more naturally from the framework. Most people I talk to haven't heard about it, and I'm surprised to see it being so applicable to so many fields. Especially interesting was when they said the theory isn't exactly equivalent in GR, leading to different calculations. Kind of crazy to see that in GA, curved spacetime isn't a thing. I'm not sure how that would work, since isn't the big picture in GR about particles moving through geodesics in curved space?

As an undergrad, I would definitely love the possibility of taking a class on it. I've seen a book that introduces linear algebra and geometric algebra together, though I haven't really gone through it that much. The author even made a textbook to teach vector calculus and geometric calculus as a natural generalization. Maybe one day I'll sit down and go through it.

u/tikael · 7 pointsr/AskPhysics

Get a copy of Div, Grad, Curl. It will walk you through the math you need.

u/fatangaboo · 7 pointsr/AskEngineers
  1. Vector Calculus isn't just a required math course, and the often-suggested supplementary textbook Div, Grad, Curl, and All That has a terribly misleading title - VC's not just a temporary annoyance, you'll actually need this stuff later.

  2. Same for probability. If you skate thru probability hoping you can forget it right away, you're gonna have a bad time in your Signals classes and your Communications classes later. Stochastic Processes will strangle you and urinate on your corpse.

  3. During your internship(s), do your best to befriend the engineers you work around & with. They have much to teach you and can give you excellent advice after your internship is over. Plus they can write letters of reference that are a lot more influential than your Logic Design professor can write.

  4. No matter how much you enjoyed your Chemistry classes, and no matter how well you did in them, it turns out that Chemistry is 99% irrelevant to EE. Sorry.

  5. Programming and software are a fact of EE life. Become a good coder and don't let your skills atrophy. Learn Linux or at least UNIX or at least the UNIX underpinnings of MAC OSX. Learn command line tools.

  6. Often the best EEs are the ones with the most bravery, the least afraid of the unknown. "I've never done that before" is a reason to jump in and try something, NOT an excuse to back away.

  7. Analysis Paralysis really does exist. Avoid it.
u/stackrel · 6 pointsr/math

I don't think you'll "spoil" what you'll learn later. If anything, seeing the material before will help you understand cooler stuff during the class next year. There's a lot of remarks and subtle examples I missed the first time I went through the standard undergrad math topics, that I only learned later.

But if you still want to avoid the topics you'll see in class, you could try some point-set topology (e.g. Munkres Topology). It would be beneficial for the real analysis class too. For differential geometry, I'd recommend Jänich Vector Analysis, which says it only needs calculus and linear algebra as prereqs.

u/B-80 · 6 pointsr/Physics

Read this for the basic algebriac perspective (really only need the super short first chapter on tensors), then this for the application to general relativity, which is, to a good approximation, just tensor analysis on manifolds (mainly chapter 2 and 3).

u/[deleted] · 6 pointsr/Physics

J.F. Cornwell, Group theory in physics: an introduction (link)

W. Ludwig, Symmetries in physics: group theory applied to physical problems(link)

M. Tinkham, Group theory and quantum mechanics (link)

W.-K. Tung, Group theory in physics (link)

E.P. Wigner, Group theory and its applications to the quantum mechanics of atomic spectra (link1, link2)

N. Jeevanjee, An Introduction to Tensors and Group Theory for Physicists (link)

G. Costa, Symmetries and Group Theory in Particle Physics: An Introduction to Space-Time and Internal Symmetries (link)

B. Hall, Lie Groups, Lie Algebras, and Representations: An Elementary Introduction (link)

R. McWeeny, Symmetry: An Introduction to Group Theory and Its Applications (Dover Books on Physics)(link)

u/dolichoblond · 5 pointsr/math

same here. In the rush to get everyone ok with matrix arithmetic, I feel like most students never realized that the matrix was just a nifty way to do bookkeeping. And it's not a bad thing; it's a great tool to use and if you're on the STE side of STEM majors there might not be a lot of reason to go above it. But it does make for a wild transition when/if you ever go up a level in abstraction.

I, for example, had no idea at all. Then I was helping a friend with some programming and we stumbled onto quaternions for 6DoF modeling. Talk about a 180. I feel like I'm still re-wiring all of my algebraic understanding from that point backwards. This book was fun to read when I made that turn too.

u/shivstroll · 5 pointsr/Physics

A commonly used book for this exact purpose is Div, Grad, Curl by Schey.

u/yangyangR · 5 pointsr/Physics

I recommend Tensors Demystified

Think of them as bras and kets. The downsies indices are bra like, they eat kets and spit out c-numbers. The upsies are ket like, they correspond to the original vector space. You can combine them to give two indices in the same manner as taking the tensor product of two or more kets to get the full state.

u/Edelsonc · 5 pointsr/math

For multivariable calculus I cannot recommend Div, Grad, Curl and All That enough. It’s got wonderful physically motivated examples and great problems. If you work through all the problems you’ll have s nice grasp on some central topics of vector calculus. It’s also rather thin, making it feel approachable for self learning (and easy to travel with).

u/Aeschylus_ · 4 pointsr/Physics

You're English is great.

I'd like to reemphasize /u/Plaetean's great suggestion of learning the math. That's so important and will make your later career much easier. Khan Academy seems to go all through differential equations. All of the more advanced topics they have differential and integral calculus of the single variable, multivariable calculus, ordinary differential equations, and linear algebra are very useful in physics.

As to textbooks that cover that material I've heard Div, Grad, Curl for multivariable/vector calculus is good, as is Strang for linear algebra. Purcell an introductory E&M text also has an excellent discussion of the curl.

As for introductory physics I love Purcell's E&M. I'd recommend the third edition to you as although it uses SI units, which personally I dislike, it has far more problems than the second, and crucially has many solutions to them included, which makes it much better for self study. As for Mechanics there are a million possible textbooks, and online sources. I'll let someone else recommend that.

u/timshoaf · 4 pointsr/learnmachinelearning

/u/LengthContracted this is a good book, as is Daphne Kollers book on PGMs as well as the associated course http://pgm.stanford.edu

A sample of what is on my reference shelf includes:

Real and Complex Analysis by Rudin

Functional Analysis by Rudin

A Book of Abstract Algebra by Pinter

General Topology by Willard

Machine Learning: A Probabilistic Perspective by Murphy

Bayesian Data Analysis Gelman

Probabilistic Graphical Models by Koller

Convex Optimization by Boyd

Combinatorial Optimization by Papadimitriou

An Introduction to Statistical Learning by James, Hastie, et al.

The Elements of Statistical Learning by Hastie, et al.

Statistical Decision Theory by Liese, et al.

Statistical Decision Theory and Bayesian Analysis by Berger

I will avoid listing off the entirety of my shelf, much of it is applications and algorithms for fast computation rather than theory anyway. Most of those books, though, are fairly well known and should provide a good background and reference for a good deal of the mathematics you should come across. Having a solid understanding of the measure theoretic underpinnings of probability and statistics will do you a great deal--as will a solid facility with linear algebra and matrix / tensor calculus. Oh, right, a book on that isn't a bad idea either... This one is short and extends from your vector classes

Tensor Calculus by Synge

Anyway, hope that helps.

Yet another lonely data scientist,

Tim.

u/joshuahutt · 4 pointsr/math

Not sure if they qualify as "beautifully written", but I've got two that are such good reads that I love to go back to them from time to time:

u/poopstixPS2 · 3 pointsr/EngineeringStudents

I looked at the free pages on Amazon and it does seem a bit wordier than the physics books I remember. It could just be the chapter. Maybe it reads like a book; maybe it's incredibly boring :/

If money isn't an issue (or if you're resourceful and internet savvy ;) you can try the book by Serway & Jewett. It's fairly common.

http://www.amazon.com/Physics-Scientists-Engineers-Raymond-Serway/dp/1133947271

As for DE, this book really resonated with me for whatever reason. Your results may vary.

http://www.amazon.com/Course-Differential-Equations-Modeling-Applications/dp/1111827052/ref=sr_1_2?s=books&ie=UTF8&qid=1372632638&sr=1-2&keywords=differential+equations+gill

If your issue is with the technical nature of textbooks in general, then you'll either have to deal with it or look for some books that simplify/summarize the material in some way. The only example I can come up with is:

http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393925161/ref=sr_1_1?s=books&ie=UTF8&qid=1372632816&sr=1-1&keywords=div+grad+curl

Although Div, Grad, Curl, and all That is intended for students in an Electromagnetics course (not Physics 2), it might be helpful. It's an informal overview of Calculus 3 integrals and techniques. The book uses electromagnetism in its examples. I don't think it covers electric circuits, which are a mess of their own. However, there are tons of resources on the internet for circuits. I hope all this was helpful :)

u/freireib · 3 pointsr/Physics

Are you familiar with Div, Grad, Curl, & All That. If not you'd probably enjoy it.

u/adventuringraw · 3 pointsr/learnmachinelearning

let me give you a shortcut.

You want to know how partial derivatives work? Consider a function with two variables: f(x,y) = x^2 y^3, for a simple example.

here's what you do. Let's take the partial derivative with respect to x. What you do, is you consider all the other variables to be constant, and just take the standard derivative with respect to x. In this case, the partial derivative with respect to x is: 2xy^3. That's it, it's really that easy.

What about taking with respect to y? Same thing, now x is constant, and your answer is 3x^2 y^2.

This is an incredibly deep topic, but getting enough of an understanding to tackle gradient descent is really pretty simple. If you want to full on jump in though and get some exposure to way more than you need, check out div curl and grad and all that. It covers a lot, including a fair amount that you won't need for any ML algorithm I've ever seen (curl, divergence theorem, etc) but the intro section on the gradient at the beginning might be helpful... maybe see if you can find a pdf or something. There's probably other good intros too, but seriously... the mechanics of actually performing a partial derivative really are that easy. If you can do a derivative in one dimension, you can handle partial derivatives.

edit: I misread, didn't see you were a junior in highschool. Disregard div curl grad and all that, I highly recommend it, but you should be up through calc 3 and linear algebra first.

To change my advice to be slightly more relevant, learn how normal derivatives work. Go through the Kahn Academy calc stuff if the format appeals to you. Doesn't matter what course you go through though, you just need to go through a few dozen exercises (or a few hundred, depending on your patience and interest) and you'll get there. Derivatives aren't too complicated really, if you understand the limit definition of the derivative (taking the slope over a vanishingly small interval) then the rest is just learning special cases. How do you take the derivative of f(x)g(x)? f(g(x))? There's really not too many rules, so just spend a while practicing and you'll be right where you need to be. Once you're there, going up to understanding partial derivatives is as simple as I described above... if you can take a standard derivative, you can take a partial derivative.

Also: props for wading into the deep end yourself! I know some of this stuff might seem intimidating, but if you do what you're doing (make sure you understand as much as you can instead of blowing ahead) you'll be able to follow this trail as far as you want to go. Good luck, and feel free to hit me up if you have any specific questions, I'd be happy to share.

u/jacobolus · 3 pointsr/math

You might enjoy Parry Moon’s Theory of Holors. There’s a whole cornucopia of obscure names for number-like things, https://www.amazon.com/Theory-Holors-Parry-Hiram-Moon/dp/0521019001 https://en.wikipedia.org/wiki/Parry_Moon#Holors

Instead of “-ions” though, we get “merates”.

u/InfanticideAquifer · 3 pointsr/Physics

I thought that Marsden and Tromba was a pretty good book. It does a lot of stuff in n-dimensions, which you wouldn't need for E&M, but everything is there and it is computation oriented, rather than "proofy". You know it's good for physics because it has a picture of Newton on the front!

u/totallynotshilling · 2 pointsr/AskPhysics

Haven't used it myself, but you might want to check out Div,Grad,Curl by Schey.

u/lewisje · 2 pointsr/learnmath

For vector calculus, you might enjoy the less formal British text Div, Grad, Curl, and All That by H. M. Schey; for group theory in brief, consider the free textbook Elements of Abstract and Linear Algebra by Edwin H. Connell.

Alternatives to Schey's book include the much more formal Calculus on Manifolds by Michael Spivak, which does have more exercises than Schey but uses most of them to develop the theory, rather than as the mindless drills that fill an ordinary textbook; Michael E. Corral's free textbook Vector Calculus isn't huge but is written closer to an ordinary textbook.

u/nmw2 · 2 pointsr/math

Precalculus is not an actual field, so I do not know what exactly is taught in the class, but the best book I know of on analysis would be A Course of Pure Mathematics - G.H. Hardy

u/Antagonist360 · 2 pointsr/math

I found the book Div Grad Curl and All That to explain it pretty well. The book is short enough to read through in a couple hours.

u/chinchilla_of_gree · 2 pointsr/math

Although it has already been answered, I recommend the book "Tensors, Differential Forms and Variational Principles" by Lovelock and Rund. From what I gather, you are looking for a more analytic approach and this is exactly what that book offers. It's a Dover publication, hence it is very cheap (currently under $10).
Link to its American amazon page

u/WailingFungus · 2 pointsr/Physics

I found this book quite useful for an intro to group theory.

u/rcochrane · 2 pointsr/math

> Second and third semester calculus

Is this vector calc? If so I enjoyed this book as it's very geometric, not at all rigorous and has lots of worked examples and exercises. Sorry it seems to be so expensive -- it wasn't when I bought it, and hopefully you can find it a lot cheaper if it's what you're looking for.

In general Stewart's big fat calculus book is a nice thing to have for autodidacts.

Obviously what you describe might include analysis, which these books won't help with.

>Formal logic theory (Think Kurt Godel)

I've heard Peter Smith's book on Godel is good, but haven't read it. Logic is a huge field and it depends a lot on what your background is and what you want to get out of it. You may need a primer on basic logic first; I like this one but again it's quite personal.

u/bobovski · 2 pointsr/math

I don't know about adsfgk, but I recommend Lovric.

u/testcase51 · 2 pointsr/PhysicsStudents

As others have mentioned, there are a lot of good books on Math Methods of Physics out there (I used Hassani's Mathematical Methods: For Students of Physics and Related Fields).

That said, if you're having trouble with calculus, I'd recommend going back and really understanding that well. It underlies more or less all the mathematics found in physics, and trying to learn vector calculus (essential for E&M) without having a solid understanding of single-variable calculus is just asking for trouble.

There are a number of good books out there. Additionally, Khan Academy covers calculus very well. The videos on this page cover everything you'd encounter in your first year, and maybe a smidge more.

Once you move on to vector calculus, Div, Grad, Curl and All That is without equal.

u/throwaway_entreprene · 2 pointsr/math

Most of the books by John Stillwell, Klaus Jänich and John Conway. In particular, The Four Pillars of Geometry ,Numbers and Geometry, Vector Analysis, Topology

u/MedPhysPHD · 2 pointsr/berkeley

Math 53 isn't heavy on proofs at all except possibly near the tail end of the course. Actually, the whole purpose of Math 53 really is the last 2 weeks when it gets into the Stoke's and Divergence Theorem. If you want to get started early on that I recommend the excellent Div, Grad, Curl, and All That which is a short text you can get online or the library that really makes the topic more manageable. Be prepared for it because it will hit you right at the end of the semester although the curve is generally nicer than Math 1B.

Math 54, or linear algebra in general, is for a lot of people the "intro to proofs" course. Right around the time Math 53 goes at breakneck speed, Math 54 finishes up with fourier analysis. It's doable but you have to stay on top of things the whole semester or have a miserable few weeks near the end.

u/mrcmnstr · 2 pointsr/Physics

I thought of some books suggestions. If you're going all in, go to the library and find a book on vector calculus. You're going to need it if you don't already know spherical coordinates, divergence, gradient, and curl. Try this one if your library has it. Lots of good books on this though. Just look for vector calculus.

Griffiths has a good intro to E&M. I'm sure you can find an old copy on a bookshelf. Doesn't need to be the new one.

Shankar has a quantum book written for an upper level undergrad. The first chapter does an excellent job explaining the basic math behind quantum mechanics .

u/SquirrelicideScience · 2 pointsr/math

Is it this one?

u/Valeen · 2 pointsr/askscience

As SDogwood said you need an intro in proofs. Unfortunately I know of no better way to do this than to sit in on a class such as "intro to abstract algebra", I took it as a junior level course. I can't even tell you what book to use, cause the prof wrote their own ~100 page book and sold it as notes for like $5. The most difficult part of the class was actually having the will power to show up. I did almost no work outside of the class. One of the things that the department required the class do is make the students present a proof, normally 3 students at the beginning of class and you would rotate through the roster. Shockingly it was one of the more fun classes I took. If you can do this it is probably your best option. I know engineering curriculums can be tight, but you really should see if maybe there is a night version or something, its worth it.

I would also suggest just picking out some dover books like this one and working through it on your own. Stuff like that you won't need proofs for and depending on what type of engineer you are may also be of help.

u/krypton86 · 2 pointsr/ECE

For vector calculus: Div, Grad, Curl, and All That: An Informal Text on Vector Calculus

For complex variables/Laplace: Complex Variables and the Laplace Transform for Engineers - Caution! Dover book! Slightly obtuse at times!

For the finite difference stuff I would wait until you have a damn good reason to learn it, because there are a hundred books on it and none of them are that good. You're better off waiting for a problem to come along that really requires it and then getting half a dozen books on the subject from the library.

I can't help with the measurement text as I'm a physicist, not an engineer. Sorry. Hope the rest helps.

u/TheAntiRudin · 2 pointsr/math

Functions of One Complex Variable I & II by John Conway.

u/Figowitz · 1 pointr/Physics

For your calculus brush-up, I would wholeheartedly recommend Calculus Made Easy by Silvanus P. Thompson. Available as pdf here or a newer, revised edition from Amazon here in which Martin Gardner has updated terminology, notation and such, as well as adding some excellent introductory chapters that help with the intuition. It is a deceptively small book with around 300 A5 sized pages, but it delivers most everything you need to know about calculus, including many handy tricks, in a intuitive down to earth style. Each chapter has a bunch of problems of varying degree along with solutions in the appendix. To top it off, Richard Feynmann was introduced to calculus from this book too...

In my opinion, a solid and intuitive understanding of calculus is one of the most important aspect of understanding much of physics, and the book has certainly helped me a great deal.

Another important aspect is of course vectors, for which I enjoyed the slightly unusual treatment in About Vectors by Banesh Hoffmann, although I'm unsure if it is fitting for revisiting.

u/trengot · 1 pointr/math
u/InfiniteHarmonics · 1 pointr/math

I used this book for when I took the course:

https://www.amazon.com/Introduction-Vector-Analysis-Harry-Davis/dp/0697160998

It's a book you really need to read every word to get an understanding of all the topics. It explains the Frenet formulas well as well as the cross product. These bits of exposition may be lost on someone's first course in vector analysis. We also covered the optional sections on tensor calculus. If the students have had a proof based linear algebra course, then they will eat up tensor notation.

u/carvin_martin · 1 pointr/Physics

Favorite Book Ever

http://www.amazon.com/Geometrical-Vectors-Chicago-Lectures-Physics/dp/0226890481

Vector Calculus & Geometry. This is the clearest, most enjoyable & enlightening math book I have ever read.

u/wonkybadank · 1 pointr/math

Calc 3 was series for us, 4 was multivariable. We were quarters with summer quarter being optional so it was really trimesters for most people. Vector calc was basically taught from the book Div, Grad, Curl and All That. So it was useful prior to going into electrodynamics, which was also 4th year.

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EDIT: Added link.

u/astrophys · 1 pointr/physicsbooks

http://www.amazon.com/Introduction-Tensors-Group-Theory-Physicists/dp/0817647147/ref=sr_1_1?ie=UTF8&qid=1370289295&sr=8-1&keywords=jeevanjee

This one is probably the most intuitive description of tensors and group theory I've read, but it's not free =(

u/Arienna · 1 pointr/EngineeringStudents

There's a book called Div, Grad, Curl and All That, here is an Amazon link. It's an informal approach to vector mathematics for scientists and engineers and it's pretty readable. If you're struggling with the math, this is for you :) All their examples are EM too.

It's also a good idea to get a study group together. The blind leading the blind actually do get somewhere. :)

u/shogun333 · 1 pointr/IAmA

I have been trying to study tensor calculus in my own time. I have this and this book. I'm finding it a bit difficult. Any suggestions?

u/roshoka · 1 pointr/Physics

Late, but here are undergrad books on the subject: geometric algebra, geometric calculus.

A grad-type book that has both and their applications to physics would be this one

I'm currently learning the geometric algebra undergrad book. It's a good read so far, and the author keeps up with book errors.

u/Thoonixx · 1 pointr/math

http://www.amazon.com/dp/0471725692/ref=wl_it_dp_o_pd_S_ttl?_encoding=UTF8&colid=2UCFQZHNW5VVF&coliid=I1RPWVCSMOOV09 is one good suggestion, I've seen around here. It's on my wishlist and the book that I intend to work from.

Now I always struggled with vector calculus and its motivations. So I have this one waiting for me as well http://www.amazon.com/dp/0393925161/ref=wl_it_dp_o_pC_nS_ttl?_encoding=UTF8&colid=2UCFQZHNW5VVF&coliid=I20JETA4TTSTJY since I think it covers a lot of the concepts that I had the most trouble with in calc 3

u/a__x · 1 pointr/math

For single variable calculus, like everyone else I would recommend Calculus - Spivak. If you have already seen mechanical caluculus, mechanical meaning plug and chug type problems, this is a great book. It will teach you some analysis on the real line and get your proof writing chops up to speed.

For multivariable calculus, I have three books that I like. Despite the bad reviews on amazon, I think Vector Calculus - Marsden & Tromba is a good text. Lots of it is plug and chug, but the problems are nice.

One book which is proofed based, but still full of examples is Advanced Calculus of Several Variables - Edwards Jr.. This is a nice book and is very cheap.

Lastly, I would like to give a bump to Calculus on Manifolds - Spivak. This book is very proofed based, so if you are not comfortable with this, I would sit back and learn from of the others first.

u/Ray_Skywalker · 1 pointr/slavelabour

https://www.amazon.com/Vector-Calculus-Jerrold-Marsden/dp/1429215089

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CLOSED

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Someone has it listed here on reddit for free

u/_11_ · 1 pointr/EngineeringStudents

Div, Grad, Curl, and All That is a good way to shore up your knowledge of vector calc.

u/runs_on_command · 1 pointr/ECE

When I took EM in addition to Cheng the professor suggested getting Div, Grad, Curl and all of that. I found that to be alot of help in solidifying the math and intuition needed.

u/wo0sa · 0 pointsr/askscience

Try this.

But really it comes with practice, the more you use it, the better you get at reading it and comfortable with it. In my case at least.