Resources for learning multivariable calculus

In summary: Alternatively, there is a more recent and more detailed book on the same material, but written more for researchers and graduate students, which is:Finite-dimensional partial differential equations: an introduction to their mathematical theories and mathematical models, 3rd edition, by B.G. Haddad, R.A. Morrey, and J.A. Yorke.
  • #1
Jazzyrohan
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I have recently started studying multivariable calculus and I cannot quite visualise the concepts.Problem solving is not a problem but I want a true understanding of the concepts.Which book or online resources are great at developing visualisation in this course?
 
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  • #2
Jazzyrohan said:
I have recently started studying multivariable calculus and I cannot quite visualise the concepts.Problem solving is not a problem but I want a true understanding of the concepts.Which book or online resources are great at developing visualisation in this course?

https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/

This is where I first learned it close to 10 years ago. The lectures are a tad old but I think they are excellent assuming you would have the patience to go through it all. It is quite worth it if you do. I have never had trouble with visualising stuff or drawing intuitions in multivariate calculus thanks to this guy. The visualisations are just good old chalk-on-board though, nothing too fancy.

Also, I think visualisation may also be tied with understanding the applications of the math. The best visualisation of flux through a surface is gotten through studying it in terms of electric flux, gravitational flux or fluid flux.

Found this cool visualisation for fields that might help you out:



If you mention what concepts exactly you have trouble visualising, I might be able to help out more.

Of course there may be other excellent resources that use computer graphic animations and stuff elsewhere that maybe others could suggest.
 
  • #3
thariya said:
https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/

This is where I first learned it close to 10 years ago. The lectures are a tad old but I think they are excellent assuming you would have the patience to go through it all. It is quite worth it if you do. I have never had trouble with visualising stuff or drawing intuitions in multivariate calculus thanks to this guy. The visualisations are just good old chalk-on-board though, nothing too fancy.

Also, I think visualisation may also be tied with understanding the applications of the math. The best visualisation of flux through a surface is gotten through studying it in terms of electric flux, gravitational flux or fluid flux.

Found this cool visualisation for fields that might help you out:



If you mention what concepts exactly you have trouble visualising, I might be able to help out more.

Of course there may be other excellent resources that use computer graphic animations and stuff elsewhere that maybe others could suggest.

Thank you so much for helping me out.Can you suggest a good book too for problem solving?
 
  • #4
There are basically three fundamental theorems in several variable calculus, one about derivatives, one about integrals, and one relating the two concepts.

The first theorem is the inverse/implicit function theorem, which in its simplest form says that a smooth function from R^n to R^n whose derivative is invertible (as a linear map) at a point, is it self smoothly invertible on a neighborhood of that point. This is a higher dimensional version of the theorem in one variable that a smooth function whose tangent line is not horizontal at a point, miust be either increasing or decreasing (i.e. injective) on some interval around that point.

The second theorem tells you how to compute several variable integrals by reducing to the one variable case; this is called Fubini's theorem, i.e. a multiple integral can be computed as a repeated integral, integrating one variable at a time.

The third theorem is called Stokes' theorem, which generalizes theorems also called Green's, Gauss's, or the divergence theorem. It equates an integral over a region with boundary with another integral taken just over the boundary. This generalizes the fundamental theorem of calculus in one variable. In particular it is again true that the integrand over the bounded region is a certain derivative of the integrand over the boundary. Essentially this is proved by using Fubini's theorem to reduce to the one variable fundamental theorem.

There are also other important results such as the "change of variables" rule for integrals, and rules for interchanging the order of taking derivatives and integrals. It is also useful to know some criteria for existence, smoothness, and uniqueness of solutions to differential equations.

I see from the MIT course notes that are linked above that the text for that course is the one by my friends Henry Edwards and Dave Penney. That is a little more introductory course than the theoretical one I have sketched, for which a good but very terse treatment is in Spivak's Calculus on Manifolds. Edwards and Penney would be a better first encounter with this material.
 
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  • #5
Jazzyrohan said:
Can you suggest a good book too for problem solving?

For a book with lots of problems, try Marsden & Tromba, Vector Calculus. But be aware that the explanations and examples have been called unhelpful in reviews. (I found it to be okay though.)
 
  • #6
I taught from Marsden and Tromba to bright high school students in the 1980's and thought it was a very good book. It was produced to be used as I recall at Berkeley, so maybe not the right level for all students.
 
  • #7
Jazzyrohan said:
Thank you so much for helping me out.Can you suggest a good book too for problem solving?
Happy to help! I don't quite recall a textbook for this. I see a couple of suggestions have come in for that. Hopefully one of them will suit your need!
 
  • #8
mathwonk said:
I taught from Marsden and Tromba to bright high school students in the 1980's and thought it was a very good book. It was produced to be used as I recall at Berkeley, so maybe not the right level for all students.

Yes, it's probably a book for the B student who wants good problems to solve. But I found I understood the material better after solving the problems.
 

1. What is multivariable calculus?

Multivariable calculus is a branch of mathematics that deals with functions of several variables. It extends the concepts of single-variable calculus to functions with multiple independent variables, allowing for the analysis of more complex systems and phenomena.

2. Why is multivariable calculus important?

Multivariable calculus is used in a variety of fields, such as physics, engineering, economics, and statistics. It allows for the modeling and analysis of real-world systems with multiple variables, making it an essential tool for problem-solving and understanding complex phenomena.

3. What are some resources for learning multivariable calculus?

There are many resources available for learning multivariable calculus, such as textbooks, online courses, video lectures, and practice problems. Some popular textbooks include "Multivariable Calculus" by James Stewart and "Vector Calculus" by Jerrold E. Marsden and Anthony J. Tromba. Online resources like Khan Academy and MIT OpenCourseWare also offer free multivariable calculus courses.

4. How can I improve my understanding of multivariable calculus?

To improve your understanding of multivariable calculus, it is important to practice solving problems and working through examples. It can also be helpful to seek out additional resources, such as study groups or tutoring, and to review concepts regularly to reinforce your understanding.

5. What are some key topics covered in multivariable calculus?

Some key topics covered in multivariable calculus include partial derivatives, multiple integrals, vector calculus, and applications of multivariable calculus in physics and engineering. Other important concepts include gradient, divergence, and curl, as well as optimization and constrained optimization problems.

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