Writing a calculus book that's more rigorous than typical books is hard because if you go too hard, people will say that you've written a real analysis book and the point of calculus is to introduce certain concepts without going full analysis. This book seems to have at least avoided the trap of trying to be too rigorous about the concept of convergence and spending more time on introducing vocabulary to talk about functions and talking about intersections with linear algebra.
As a math professor who has taught calculus many times, I'd say there are many different things one could hope to learn from a calculus course. I don't think the subject distills well to a single point.
One unusual feature of calculus is that it's much easier to understand at a non-rigorous level than at a rigorous level. I wouldn't say this is true of all of math. For example, if you want to understand why the quadratic formula is true, an informal explanation and a rigorous proof would amount to approximately the same thing.
But, when teaching or learning calculus, if you're willing to say that "the derivative is the instantaneous rate of change of a function", treat dy/dx as the fraction which it looks like (the chain rule gets a lot easier to explain!), and so on, you can make a lot of progress.
In my opinion, the issue with most calculus books is that they don't commit to a rigorous or to a non-rigorous approach. They are usually organized around a rigorous approach to the subject, but then watered down a lot -- in anticipation that most of the audience won't care about the rigor.
I believe it's best to choose a lane and stick to it. Whether that's rigorous or non-rigorous depends on your tastes and interests as a learner. This book won't be for everybody, but I'd call that a strength rather than a weakness.
The rigorous form of the non-rigorous version is non-standard analysis: There really are tiny little numbers we can manipulate algebraically and we don't need the epsilon-delta machinery to do "real math". It's so commonsensical that both Newton and Leibniz invented it in that form before rigor became the fashion, and the textbook "Calculus Made Easy" was doing it that way in 1910, a half-century before Robinson came along and showed us it was rigorous all along.
> The rigorous form of the non-rigorous version is non-standard analysis
This is quite overstated. There are other approaches to infinitesimals such as synthetic differential geometry (SDG aka. smooth infinitesimal analysis) that are probably more intuitive in some ways and less so in others. SDG infinitesimals lose the ordering of hyperreals in non-standard analysis and force you to use some non-classical logic (intuitively, smooth infinitesimals are "neither equal nor non-equal to 0", wherein classical reasoning would conflate every infinitesimal with 0), but in return you gain nilpotency (d^n = 0 for any infinitesimal d) which is often regarded as a desirable feature in informal reasoning.
One of the dangers of a non rigorous approach is not being clear about relative rates. If you're not being precise you're going to confuse people when you say eg that in the limit this triangle is a right triangle. Or look at Taylor's theorem. In different limits you can say a curve is a line, a parabola, a cubic, etc.
Anyway you've already got Apostol - if it's just calculus as such get an older edition. Modern ones have extra goodies like linear algebra but have modern text book pricing (cries softly in $150/volume).
Getting an old enough edition of Apostol's "Calculus" to not include linear algebra might be a bit challenging. Linear algebra was added to both volumes in their second editions, which came out in 1967 for volume 1 and 1969 for volume 2.
The second editions are still the current edition, so no worry that you might be missing out on something if you go with used copies. If you do want new copies (maybe you can't find used copies or they are in bad shape) take a look at international editions.
A new copy of the international edition for India from a seller in India on AbeBooks is around $15 per volume plus around $19 shipping to the US. Same contents as the US edition but paperback instead of hardback, smaller pages, and rougher paper. (International editions also often replace color with grayscale but that's not relevant in this case because Apostol does not use color)).
You can also find US sellers on AbeBooks that has imported an international edition. That will be around $34 but usually with free shipping.
Indian editions sometimes have different question sets to prevent students from using them in other countries' coursework.
They also have a hologram sticker alongside a printed warning that they are not for sale or export outside of India, Nepal and a couple of other countries.
i bought a compilers book that was an Indian edition. The paper and print quality was so bad (like smudgy) that I could not read it and I didn’t think I was particularly picky about this. Not sure if I just got unlucky or if this is generally true?
>> the author’s wish to present ... mathematics, as intuitively and informally as possible, without compromising logical rigor
The books in the West in general kept getting less rigorous, with time. I don't see Asian or Russian books doing this. The audience getting less receptive to rigor and wishing for more visuals and informal talk. When they get to higher studies and research, would they be able to cope with steep curve of more formalism and rigor?
That wouldn't be who Kolmogorov complexity is named after? ("The Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program that produces the object as output.") ..Oh it is the same mathematician, Andrey Nikolaevich Kolmogorov. I see he was a major figure with many other concepts, equations and theorems named after him.
It is very good and has a succinct coverage of a broad range of topics from Mathematics; just the right understandable level of rigor without being overwhelming.
> The books in the West in general kept getting less rigorous, with time.
I wonder if it's because more people are going to college who would have otherwise gone to a vocational or trade school? If the audience expands to include people who might not have studied calculus had they not chosen to go to college, I feel like textbooks have to change to accommodate that.
There are less formal math books in Russian. My absolute favorite calculus textbook is Fikhtenholts's "A Course of Differential and Integral Calculus". It is a bit less formal than many modern texts, but somehow much more approachable.
My pet peeve about calculus books is that they almost always overlook the importance of continuity. In some extreme cases, they even start with infinitely small sequences, with some rather gnarly theorems like Bolzano–Weierstrass theorem about converging subsequences.
I think this is a mistake. It's much easier to start with continuous functions and build from there. Modern readers then can visualize the epsilon-delta formulation of limits as "zooming in" on the function. The "epsilon" is the height of the screen, and the "delta" is the "zoom level" at which the function fragment fits on the screen.
And once you "get" the idea of continuity and function limits, the other limit theorems just fall out naturally.
This may be a stupid question, but what do people usually mean when they refer to a mathematical text as being "rigorous"? Does it mean that everything is strictly proof-based rather than application-oriented?
Generally that's what it means. And also when proofs are presented, a rigorous book will go through it fully, whereas a less rigorous one might just sketch out the main ideas of the proof and leave out some of the nitty gritty details (i.e. it's less rigorous to talk about "continuity" as "you can draw it without lifting the pen" as compared to the epsilon-delta definition, but epsilon-delta is pretty detailed and for intro calculus for non-mathematicians you don't really need it).
It certainly is more painful, but it is more beneficial. It is also harder to teach, but I stand by my claim.
I'll quote Poincare:
Math is not about the study of numbers, but the relationships between them.
The difficulty and benefit of the rigor is the abstraction. Math is all about abstraction.
The abstraction makes it harder to understand how to apply these rules, but if one breaks through this barrier one is able to apply the rules far more broadly.
----
Let's take the Fundamental Theorem of Calculus as an example[0]:
f'(x) = lim_{h->0} {f(x + h) - f(x)} / {h}
Take a moment here and think about it's form. Are there equivalent ones? What do each of these symbols mean?
If you actually study this, you may realize that there are an infinite number of equations that allow us to describe a secant line. So why this one? Is there something special? (hint: yes)
Let's call that the "forward derivative". Do you notice that through the secant line explanation that the "backward derivative" also works? That is
f'(x) = lim_{h->0} {f(x) - f(x - h)} / {h}
You may also find the symmetric derivative too!
f'(x) = lim_{h->0} {f(x + h) - f(x - h)} / {2h}
In fact, you see these in computational programs all the time! The symmetric derivative even has the added advantage of error converging at an O(n^2) rate instead of O(n)! Yet, are these the same? (hint: no)
I'm betting that most classes that went through deriving the derivative did not answer these questions for you (or you don't remember). Yet, had you, you would have instantly known how to do numerical differentiation and understand the limits, pitfalls, and other subjects like FEM (Finite-Element Methods) or Computational Methods would be much easier for those who take them.
----
Yet, I still will say that this is much harder to teach. Math is about abstraction, and abstraction is simply not that easy. But abstraction is incredibly powerful, as I hope every programmer can intuitively understand. After all, all we do is deal with abstractions. One can definitely be overly abstract and it will make a program uninterpretable for most, but one also can make a program have too little abstraction, which in that case we end up writing a million variations of the same thing, taking far more lines to write/read, and making the program too complex. There is a balance, but I'd argue that if one is able to understand abstraction that it is far easier to reduce abstraction than it is to abstract.
This is just a tiny taste of what rigor holds. You are absolutely right to be frustrated and annoyed, but I hope you understand your conclusion is wrong. Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall (or both!). The frustration and pain is quite real! But it is absolutely worth it.
You are arguing for rigor, not for its didactics. Those are different.
> had you, you would have instantly known how to do numerical differentiation and understand the limits, pitfalls, and other subjects like FEM
No, you wouldn't. You would also learn things out of order. You would be exposed to things without understanding why you are learning them. People who argue this usually learn things the intuitive way (whether from rigorous material or not - what goes on in their mind isn't rigorous), and then they go back and reassess the rigor in the light of that. Then they pretend that they learned from the rigorous exposition. No, they didn't.
It is totally fine to iterate. Learn non-rigorously. Go back to it and iterate on rigor later. As it becomes necessary, and if it ever becomes necessary for your field.
> Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall
Particularly if you are learning from "rigorous" material. But then you go watch some YouTube videos to make up for the absence of didactics in your textbook.
I mean, why don't we just throw Bourbaki books at freshmen and let them sort it out without classes? They are maximally rigorous, therefore maximally great to learn from, right?
> I mean, why don't we just throw Bourbaki books at freshmen and let them sort it out without classes?
The Bourbaki group was quite famous for wanting to restructure math education. Teaching many things that are considered advanced to children. Despite not sticking around we see elements of resurgence and effectiveness.
So I'm not sure your argument of "out of order" is accurate. The order is what we make. There's no clear optimal way to teach math. Your argument hinges on that. You might argue that the current status quo is working, so why disrupt it, and I'll point around asking if you really think it's so effective when many demonstrate a lack of understanding all around us. That so many struggle with calculus is evidence itself. We need not even acknowledge that there are many children who learn this (and let's certainly not admit that it's far more common for them to learn it in unconventional ways).
> let them sort it out without classes?
To suggest I'm arguing for the elimination of educators is beyond silly. I'd hope the caliber of your arguments would match that of your diction.
The Bourbaki group was reponsible for the Mathématiques modernes movement which intended to reform basic education on rigorous math. This may be the world's best documented educational failure in history. It was tried in several countries, so the sample size isn't one. All evidence points at rigor as a terrible educational tool.
The point of Math education isn't to create a clone army of the most pedantic pure Mathematicians in Academia.
> if you really think it's so effective when many demonstrate a lack of understanding all around us. That so many struggle with calculus is evidence itself
New Maths often called a failure but there's not real clear evidence that's the case. This is especially true in America where criticism was quite high as parents were quite vocal and struggled to help their kids (remind you of a different movement?).
There is a certain irony with that too. The major criticisms were about the de-emphasis of arithmetic, arguing that this is the skill people need more. Here we are today though, where everyone has a calculator in their pocket. Plus, people still struggle with extremely basic arithmetic such as calculating a 10% tip... SAT scores are commonly pointed to as evidence, but in the same period of time Verbal skills fell even more[0]! Would you suggest that New Maths was so bad that it made people worse at English? Or maybe there's another explanation like how the number of SAT takers dramatically increased, especially from those in the bottom percentile of high school[1,2].
If you explore the NAEP data[2] there's no decline and there's been progress the entire time for math scores for ages 9, 13, and 17 (the ages that participated).
The Russians famously did very well too.
It would be even a greater irony if we concluded something was a failure because we made mathematical errors in analyzing...
Let's take the Fundamental Theorem of Calculus as an example[0]:
f'(x) = lim_{h->0} {f(x + h) - f(x)} / {h}
This isn't the Fundamental Theorem of Calculus, it's the usual definition of the derivative of a function of a single real variable. The Fundamental Theorem of Calculus establishes the inverse relationship between differentiation and integration [0].
Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall (or both!)
Ramanujan was no stranger to banging his head against the wall. My impression from Kanigel's The Man Who Knew Infinity is that his work ethic and mathematical fortitude were as astonishing as his creativity. For much of his career, he couldn't afford paper in quantity and did his hard work on stone slate, only recording the results. This could make it seem like his results were a product of pure inspiration because he left no trace of the furious activity and struggle that was involved.
From The Man Who Knew Infinity:
When he thought hard, his face scrunched up, his eyes narrowed into
a squint. When he figured something out, he sometimes seemed to talk to
himself, smile, shake his head with pleasure. When he made a mistake,
too impatient to lay down his slate pencil, he twisted his forearm toward
his body in a single fluid motion and used his elbow, now aimed at the
slate, as an eraser.
Ramanujan's was no cool, steady Intelligence, solemnly applied to the
problem at hand; he was all energy, animation, force.
I agree with this. But I don't see the students rejecting this, but the education degreed peoples who choose texts and the publishers want to make all learning for all people. This is foolish. Most people don't need to know calculus. And if you do learn it, do so with rigor so you actually learn it and not just the appearance of it, which is much much worse.
> And if you do learn it, do so with rigor so you actually learn it
This is not strictly necessary for everybody. The conceptual ideas are what are important; else you are merely doing "plug-and-chug" Maths without any understanding. You need to focus on rigor only based on your needs and at your own pace. Concepts come first Formalism comes second.
A good example; In the Principia Newton actually uses the phrase Quantity of Motion for what we define today as Momentum. The phrase is evocative and beautifully captures the main concept instead of the bland p = m x v definition which though correct and needed for calculations conveys no mental imagery.
In Mathematics one should always approach a concept/idea from multiple perspectives including (but not limited to) Imagination, Conceptual, Graphical, Symbolic, Relationship, Applications, Definition/Theorem/Proof.
Thank you for the book link! One major problem I always had with calculus was that we didn't focus nearly enough on applications of it, outside of some optimization problems, which I loved.
I originally went for engineering, and took cal I and II, then switched to cs and poof all of the math heavy stuff vanished (except maybe some LA for graphics)
Not sure I agree with 'appearance [...] is much worse'.
Given the choice between a class room of first years who believe (in themselves and) an appearance of calculus knowledge or a room of scared undergrads that recoil from any calculus-inspired argument they 'have never learnt it properly', I'll take the former. I can work with that much more easily. Sure, some things might break - but what's the worst that can happen?
We'll sort out the rigour later while we patch the bruises of overextending some analogies.
I don't like this line of argument. It applies to many things, many of which we'd laugh at for suggesting.
Most people don't need to know how to read. Most people don't need to know how to add. Most people don't need to know how to use a computer. The foolishness of these statements are all subjective and based on what one believes one "needs". Yet, I have no doubt all of these things can improve peoples lives.
I'd argue the same with calculus. While I don't compute derivatives and integrals every day[0], I certainly use calculus every day. That likely sounds weird, but it is only because one thinks that math and computation is the same. When I drive I use calculus as I'm thinking about my rates of change, not only my velocity. Understanding different easing functions[1] I am able to create a smoother ride, be safer, drive faster, and save fuel. All at the same time!
The magic of the rigor is often lost, but the magic is abstraction. That's what we've done here with the car example. I don't need to compute numbers to "do math", I only need to have an abstract formulation. To understand that multiple variables are involved and there are relationships between them, and understanding that there are concepts like a rate of change, the rate of change of the rate of change, and even the rate of change of the rate of change of the rate of change! (the jerk!)[2].
That's still math. It may not be as rigorous, but a rigorous foundation gives you a greater ability to be less rigorous at times and take advantage of the lessons.
So yes, most people "don't need calculus" but learning it can give them a lot of power in how to think. This is true for much of mathematics. You may argue that this is not how it is taught, but with that I'll agree. The inefficiency of how it is taught is orthogonal to the utility of its lessons.
[0] Is a physicist not doing math just when they do symbol manipulation? I can tell you with great confidence, and experience, that much of their job is doing math without the use of numbers. It is about deriving formulations. Relationship!
I get the argument you're making but that's a bit like saying cavemen used to do calculus as they hunt, which is a valid way of looking at this maybe but they didn't really "use calculus" just intuition. Simillarly, when learning calculus, most people do not do so at a driving course, they do it in the classroom.
If you're willing to stretch the definition of what "using" maths is then it can apply to everything and that devalues the concept as a whole. I'm not on the toilet, I'm doing calculus!
I understand that interpretation but it's different from what I meant.
The difference may be in two different cavemen. One throws his spear on intuition alone. The other is thinking about the speed he throws, how the animal moves, the wind, and so on. There is a formulation, though not as robust as you'd see in a physics book.
> the definition of what "using" maths is then it can apply to everything
In a sense yes.
Math is a language, or more accurately a class of languages. If you're formulating your toilet activities, then it might be math. But as you might gather, there's nuance here.
I quoted Poincaré in another comment but I'll repeat here as I think it may help reduce confusion (though may add more)
Math is not the study of numbers, but the relationships between them.
Or as the category people say "the study of dots and arrows". Anything can be a dot, but you need the arrows
Yeah, I do understand your point of view. I'm just doubting if it applies universally, like you may superimpose that assumption on the thinking caveman, but is the thinking caveman really doing the same?
Yes, technique is one thing, but being really good at throwing spears doesn't make you really good at math, is my argument. And most people will encounter maths in a formal setting while lacking the broader perspective that everything is technically "math".
Yet, we need to see the argument from the common person's view, if we're talking about calculus and learning in the traditional sense. The view you stated is quite esoteric and doesn't generalize well in this setting imo.
It's like a musician saying they see music in every action, but to most non-musicians (even if the stated thing is kind of true) that doesn't make a lot of sense etc.
> but is the thinking caveman really doing the same?
Are you projecting a continuous space onto a binary one? You'll need to be careful about your threshold and I'm pretty sure it'll just make everything I said complete nonsense. If you must use a discrete space then allocate enough bins to recognize that I clearly stated there's a wide range of rigor. Obviously the caveman example is on the very low end of this.
> It's like a musician saying they see music in every action, but to most non-musicians (even if the stated thing is kind of true) that doesn't make a lot of sense etc.
Exactly. So ask why the musician, who is certainly more expert than the non-musician has a wider range? They have expertise in the matter, are you going to just ignore that simply because you do not understand? Or are you going to try to understand?
The musician, like the mathematician, understands that every sound is musical. If you want to see this in action it's quite enlightening[0]. I'm glad you brought up that comparison because I think it can help you understand what I really mean. There is depth here. Every human has access to the sounds but the training is needed to put them together and make these formulations. Benn here isn't exactly being formal writing his music using a keyboard and formalizing it down to musical notes on a sheet (though this is something I know he is capable of).
But maybe I should have quoted Picasso instead of Poincaré
Learn the rules like a pro, so you can break them like an artist.
His abstract nature to a novice looks like something they could do (Jackson Pollocks is a common example) but he would have told you he couldn't have done this without first mastery of the formal art first.
I know this is confusing and I wish I could explain it better. But at least we can see that regardless of the field of expertise we find similar trains of thought. Maybe a bridge can be created by leveraging your own domain of expertise
Maybe I can put it this way: gibberish is more intelligible when crafted by someone who can already speak.
If you care about getting all the nitty gritty details of a "rigorous" proof, maybe the quicker approach is to install Lean on your computer and step through a machine-checked proof from Mathlib. What you get from even the most heavyweight math books is still quite far from showing you all the steps involved.
Nope, but mathematics research is one of the most rarefied fields being extremely difficlt to get into, hard to get money, etc. -- (this is my understanding, at least). Progress is made here by people who, aged 10 are already showing signs of capability.
There's not much need for a large amount of PhD places, and funding, for pure mathematics research.
Likewise, on the applied side, "calculus" now as a pure thing has been dead alone time. Gradients are computed with algorithms and numerical approximations, that are better taught -- with the formal stuff maintained via intuition.
I'm much more open to the idea that the west has this wrong, and we should be more focused on developing the applied side after spending the last century overly focused on the pure
It correlates student loans with the destruction of academic integrity. The idea is school administrators want to capture as many student loan dollars as possible, and that means maximizing the number of enrolled students. To that end, complexity, rigor and difficulty are all reduced as much as possible. Students are prevented from failing, since if they fail they might drop out, reducing profits. I even remember one article which draws comparisons with russian education.
So far, I've only had a brief look at this book and what I've seen I like very much.
Many of us—especially those of us who aren't mathematically gifted—learn mathematics in ways that mostly involve procedures, rules and mechanical manipulation rather than through a rigorous step-by-step theoretical framework (well, anyway that's how I leaned the subject).
Somehow I absorbed those foundations more by osmosis than though a full understanding as my early teachers were more concerned with bashing the basics into my head. Sure, later on when confronted with advanced topics I was forced into more rigorous thinking but it wasn't uniform across the whole field.
What I really like about this book is that it confronts people like me who've already learned mathematics to a reasonably advanced level to review those fundamental concepts. The subject of 'What is Calculus?' doesn't start until Chapter 6, p223, and 'Differentiation' at Ch 8, p261. Those first 200 or so pages not only provide a comprehensive and clearly explained overview of those basic fundamentals but they ensure the reader has good understanding of them before the main subject is introduced.
I'd highly recommend this book either as a refresher or as an adjunct to one's current learning.
I don't think they are unifiable, the aims and methods one needs to learn are just too different. Limits of covering boxes and scaling your epsilons and so on, stuff from Tao's class on analysis is far away from being able to deal either non-trivial differential equations or stability analysis. You can prove all sorts of things about dense subspaces of Hilbert space and still get totally lost in multiple scale analysis, and vice versa. (Ed: epsilon was spelled espikon)
Honest question: what kind of rigor and abstraction can help us apply maths to solve problems? Don't get me wrong: I enjoy studying abstract maths and was pretty good at it in school. It's just that when it comes to what to study to make one a more effective problem solver in engineering, I was wonder I can best allocate time. For instance, I find studying probability models more helpful than studying the measure theory when it comes to applied data science or statistics. I also find studying books like Mathematical Methods for Physics and Engineering, which focuses a lot more on intuition and applications than rigor, is more effective for me than going pure math books.
I'm probably dating myself, but at my college, there was one calculus course for everybody. But also, a lot of the students in those areas had overlapping or double majors. For instance I majored in math and physics.
Perhaps the bigger question is whether it's at the right level of difficulty for the audience.
I think there are usually two: Calculus for scientists and engineers which is analytical and has lots of symbols, and Calculus for everyone else which is more practical.
Math majors might have their own. I also know they end up taking complex Calculus.
Thinking about it, ours was a small college -- 2500 students. So there may have been a practical reason for everybody taking the same math courses. They were taught more as "service" courses for the sciences and engineering than as theoretical math courses. And the students who didn't need calculus typically satisfied their math requirement with a statistics course.
Complex analysis and real analysis were among the higher-level courses, attended mostly by math majors, with the proviso that there were a lot of double majors. That was where it got interesting.
The requirements for the physics major were only a handful of math credits shy of the math major.
>The requirements for the physics major were only a handful of math credits shy of the math major.
lol, that's how I ended up with a math major. Got lost in the physics (realized I had no intuition for what was actually happening, just manipulating equations) took a couple extra courses, and boom! Math!
Without minimizing the quality or your book, I actually like subject matter books that encompass prerequisite knowledge into the text without forcing the reader to read another book in parallel (e.g. Calculus for Machine Learning by Jason Brownlee or No Bullshit Guide to Math & Physics by Ivan Savov). Though not saying that these books are better, they appeal to my learning style a bit more. Learning institutions tend to force students to take too many courses in parallel when they should find a way to join the subjects, whenever possible, without having to break the instruction into multiple semesters, just to sell more books.
This one is a hard pass. The book needs tighter editing and more rigorous reviewing.
It tries to serve all at once, but ends up in an awkward middle ground. Not deep enough to function as a real analysis text for Mathematicians, yet full of proofs that Scientists and Engineers do not care about, while failing to deliver the kind of practical rigor, those groups need when using calculus as a tool.
I really appreciate author’s effort and for releasing the PDF to the public. There are however areas I think could be made more helpful.
In the chapter on Trigonometric Functions, it begins with discussion of the derivative of the exponential function is itself, and then moves on to define sine and cosine via second degree derivatives. While interesting, this may not be the most helpful approach for intended readers.
The following chapter on Taylor Series also starts with a long discussion about the value of e. It is interesting, but it can feel a bit distracted from the main topic. The treatment of Taylor polynomials might benefit from a different approach similar to other texts.
I used LLM to rewrite above comment to make it sounds less negative. Then I read those two chapters again. This book adds complexities to simple concepts. There are good math books for non-math majors, but this isn't one of them.
While not every student is expected to read the book sequen-
tially cover to cover, it is important to have the details in one place.
Calculus is not a subject that can be learned in one pass. Indeed, this
book nearly assumes readers have already had a year of calculus, as had
the students of MAT 157Y. I hope this book will grow with its readers,
remaining both readable and informative over multiple traversals, and
that it provides a useful bridge between current calculus texts and more
advanced real analysis texts.
>Calculus is an important part of the intellectual tradition handed down
to us by the Ancient Greeks.
No it isn't? It was discovered by Newton and Leibnitz. If they're talking about Archimedes and integrals, I seem to recall his work on that was only rediscovered through a palimpsest in the last couple of decades and it contributed nothing towards Newton and Leibnitz's work.
Calculus was actually pioneered by the Kerala School of mathematicians in India during the European Middle Ages, several centuries prior to Newton and Leibniz popularizing it in Europe. The Indian texts were also quite well known to Europeans by that time, it was nowhere close to an independent discovery.
"Bhāskara II (c. 1114–1185) was acquainted with some ideas of differential calculus and suggested that the "differential coefficient" vanishes at an extremum value of the function.[18] In his astronomical work, he gave a procedure that looked like a precursor to infinitesimal methods. [...] In the 14th century, Indian mathematicians gave a non-rigorous method, resembling differentiation, applicable to some trigonometric functions. Madhava of Sangamagrama and the Kerala School of Astronomy and Mathematics stated components of calculus. They studied series equivalent to the Maclaurin expansions of [redacted] more than two hundred years before their introduction in Europe. [...] however, were not able to 'combine many differing ideas under the two unifying themes of the derivative and the integral, show the connection between the two, and turn calculus into the great problem-solving tool we have today.'"
Archimedes had functionally developed a method of integration (which was how he obtained results like volume/surface area of a sphere, or centre of mass of a hemisphere) in a manuscript that got lost to time and then rediscovered in a palimpsest (pasted and written over with a religious text)
"Laying the foundations for integral calculus and foreshadowing the concept of the limit, ancient Greek mathematician Eudoxus of Cnidus (c. 390–337 BC) developed the method of exhaustion to prove the formulas for cone and pyramid volumes.
"During the Hellenistic period, this method was further developed by Archimedes (c. 287 – c. 212 BC), who combined it with a concept of the indivisibles—a precursor to infinitesimals—allowing him to solve several problems now treated by integral calculus. In 'The Method of Mechanical Theorems' he describes, for example, calculating the center of gravity of a solid hemisphere, the center of gravity of a frustum of a circular paraboloid, and the area of a region bounded by a parabola and one of its secant lines."
Writing a calculus book that's more rigorous than typical books is hard because if you go too hard, people will say that you've written a real analysis book and the point of calculus is to introduce certain concepts without going full analysis. This book seems to have at least avoided the trap of trying to be too rigorous about the concept of convergence and spending more time on introducing vocabulary to talk about functions and talking about intersections with linear algebra.
> The point of calculus is...
As a math professor who has taught calculus many times, I'd say there are many different things one could hope to learn from a calculus course. I don't think the subject distills well to a single point.
One unusual feature of calculus is that it's much easier to understand at a non-rigorous level than at a rigorous level. I wouldn't say this is true of all of math. For example, if you want to understand why the quadratic formula is true, an informal explanation and a rigorous proof would amount to approximately the same thing.
But, when teaching or learning calculus, if you're willing to say that "the derivative is the instantaneous rate of change of a function", treat dy/dx as the fraction which it looks like (the chain rule gets a lot easier to explain!), and so on, you can make a lot of progress.
In my opinion, the issue with most calculus books is that they don't commit to a rigorous or to a non-rigorous approach. They are usually organized around a rigorous approach to the subject, but then watered down a lot -- in anticipation that most of the audience won't care about the rigor.
I believe it's best to choose a lane and stick to it. Whether that's rigorous or non-rigorous depends on your tastes and interests as a learner. This book won't be for everybody, but I'd call that a strength rather than a weakness.
The rigorous form of the non-rigorous version is non-standard analysis: There really are tiny little numbers we can manipulate algebraically and we don't need the epsilon-delta machinery to do "real math". It's so commonsensical that both Newton and Leibniz invented it in that form before rigor became the fashion, and the textbook "Calculus Made Easy" was doing it that way in 1910, a half-century before Robinson came along and showed us it was rigorous all along.
https://calculusmadeeasy.org/
https://en.wikipedia.org/wiki/Calculus_Made_Easy
> The rigorous form of the non-rigorous version is non-standard analysis
This is quite overstated. There are other approaches to infinitesimals such as synthetic differential geometry (SDG aka. smooth infinitesimal analysis) that are probably more intuitive in some ways and less so in others. SDG infinitesimals lose the ordering of hyperreals in non-standard analysis and force you to use some non-classical logic (intuitively, smooth infinitesimals are "neither equal nor non-equal to 0", wherein classical reasoning would conflate every infinitesimal with 0), but in return you gain nilpotency (d^n = 0 for any infinitesimal d) which is often regarded as a desirable feature in informal reasoning.
One of the dangers of a non rigorous approach is not being clear about relative rates. If you're not being precise you're going to confuse people when you say eg that in the limit this triangle is a right triangle. Or look at Taylor's theorem. In different limits you can say a curve is a line, a parabola, a cubic, etc.
Anyway you've already got Apostol - if it's just calculus as such get an older edition. Modern ones have extra goodies like linear algebra but have modern text book pricing (cries softly in $150/volume).
Getting an old enough edition of Apostol's "Calculus" to not include linear algebra might be a bit challenging. Linear algebra was added to both volumes in their second editions, which came out in 1967 for volume 1 and 1969 for volume 2.
The second editions are still the current edition, so no worry that you might be missing out on something if you go with used copies. If you do want new copies (maybe you can't find used copies or they are in bad shape) take a look at international editions.
A new copy of the international edition for India from a seller in India on AbeBooks is around $15 per volume plus around $19 shipping to the US. Same contents as the US edition but paperback instead of hardback, smaller pages, and rougher paper. (International editions also often replace color with grayscale but that's not relevant in this case because Apostol does not use color)).
You can also find US sellers on AbeBooks that has imported an international edition. That will be around $34 but usually with free shipping.
I know where my confusion comes from.
I studied from a first edition of volume one before there was a volume two, so it wasn't marked as Vol I.
Friend dug it up from his old books, since I seemed to be quick learner.
Indian editions sometimes have different question sets to prevent students from using them in other countries' coursework.
They also have a hologram sticker alongside a printed warning that they are not for sale or export outside of India, Nepal and a couple of other countries.
I think those restrictions apply only to retail sellers in those countries, not to purchasers or used stores.
Thanks for the info on cheaper editions, not important to me but to others in USA it might be a big help.
i bought a compilers book that was an Indian edition. The paper and print quality was so bad (like smudgy) that I could not read it and I didn’t think I was particularly picky about this. Not sure if I just got unlucky or if this is generally true?
Spivak's book is still good too.
>> the author’s wish to present ... mathematics, as intuitively and informally as possible, without compromising logical rigor
The books in the West in general kept getting less rigorous, with time. I don't see Asian or Russian books doing this. The audience getting less receptive to rigor and wishing for more visuals and informal talk. When they get to higher studies and research, would they be able to cope with steep curve of more formalism and rigor?
> Russian books doing this.
Mathematics: Its Content, Methods and Meaning by A.D. Aleksandrov, A.N. Kolomogorov, M.A. Lavrent’ev,.. https://www.goodreads.com/book/show/405880.Mathematics
It's still a masterpiece. Originally published in 1962 in 3 volumes. The English translation has all in one.
> A.N. Kolomogorov
That wouldn't be who Kolmogorov complexity is named after? ("The Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program that produces the object as output.") ..Oh it is the same mathematician, Andrey Nikolaevich Kolmogorov. I see he was a major figure with many other concepts, equations and theorems named after him.
is that like a Landau Lifshitz for Math?
It is very good and has a succinct coverage of a broad range of topics from Mathematics; just the right understandable level of rigor without being overwhelming.
Published by Dover Publications and hence quite affordable. See ToC at https://store.doverpublications.com/products/9780486409160
No, it's just a gentle overview.
> The books in the West in general kept getting less rigorous, with time.
I wonder if it's because more people are going to college who would have otherwise gone to a vocational or trade school? If the audience expands to include people who might not have studied calculus had they not chosen to go to college, I feel like textbooks have to change to accommodate that.
Non-STEM curricula do not necessarily require calculus.
There are less formal math books in Russian. My absolute favorite calculus textbook is Fikhtenholts's "A Course of Differential and Integral Calculus". It is a bit less formal than many modern texts, but somehow much more approachable.
My pet peeve about calculus books is that they almost always overlook the importance of continuity. In some extreme cases, they even start with infinitely small sequences, with some rather gnarly theorems like Bolzano–Weierstrass theorem about converging subsequences.
I think this is a mistake. It's much easier to start with continuous functions and build from there. Modern readers then can visualize the epsilon-delta formulation of limits as "zooming in" on the function. The "epsilon" is the height of the screen, and the "delta" is the "zoom level" at which the function fragment fits on the screen.
And once you "get" the idea of continuity and function limits, the other limit theorems just fall out naturally.
This may be a stupid question, but what do people usually mean when they refer to a mathematical text as being "rigorous"? Does it mean that everything is strictly proof-based rather than application-oriented?
Generally that's what it means. And also when proofs are presented, a rigorous book will go through it fully, whereas a less rigorous one might just sketch out the main ideas of the proof and leave out some of the nitty gritty details (i.e. it's less rigorous to talk about "continuity" as "you can draw it without lifting the pen" as compared to the epsilon-delta definition, but epsilon-delta is pretty detailed and for intro calculus for non-mathematicians you don't really need it).
This is the reason that everyone at my university said to just take the Applied version of Calculus 1 and 2 t avoid the proofs.
Rigorous = a pain in the ass to learn from, but you gain imaginary points for the pain.
It certainly is more painful, but it is more beneficial. It is also harder to teach, but I stand by my claim.
I'll quote Poincare:
The difficulty and benefit of the rigor is the abstraction. Math is all about abstraction.The abstraction makes it harder to understand how to apply these rules, but if one breaks through this barrier one is able to apply the rules far more broadly.
Let's take the Fundamental Theorem of Calculus as an example[0]: Take a moment here and think about it's form. Are there equivalent ones? What do each of these symbols mean?If you actually study this, you may realize that there are an infinite number of equations that allow us to describe a secant line. So why this one? Is there something special? (hint: yes)
Let's call that the "forward derivative". Do you notice that through the secant line explanation that the "backward derivative" also works? That is
You may also find the symmetric derivative too! In fact, you see these in computational programs all the time! The symmetric derivative even has the added advantage of error converging at an O(n^2) rate instead of O(n)! Yet, are these the same? (hint: no)Or tell me about the general case of
I'm betting that most classes that went through deriving the derivative did not answer these questions for you (or you don't remember). Yet, had you, you would have instantly known how to do numerical differentiation and understand the limits, pitfalls, and other subjects like FEM (Finite-Element Methods) or Computational Methods would be much easier for those who take them. Yet, I still will say that this is much harder to teach. Math is about abstraction, and abstraction is simply not that easy. But abstraction is incredibly powerful, as I hope every programmer can intuitively understand. After all, all we do is deal with abstractions. One can definitely be overly abstract and it will make a program uninterpretable for most, but one also can make a program have too little abstraction, which in that case we end up writing a million variations of the same thing, taking far more lines to write/read, and making the program too complex. There is a balance, but I'd argue that if one is able to understand abstraction that it is far easier to reduce abstraction than it is to abstract.This is just a tiny taste of what rigor holds. You are absolutely right to be frustrated and annoyed, but I hope you understand your conclusion is wrong. Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall (or both!). The frustration and pain is quite real! But it is absolutely worth it.
[0] Linking an EpsilonDelta video that covers this exact example in more detail https://www.youtube.com/watch?v=oIhdrMh3UJw
You are arguing for rigor, not for its didactics. Those are different.
> had you, you would have instantly known how to do numerical differentiation and understand the limits, pitfalls, and other subjects like FEM
No, you wouldn't. You would also learn things out of order. You would be exposed to things without understanding why you are learning them. People who argue this usually learn things the intuitive way (whether from rigorous material or not - what goes on in their mind isn't rigorous), and then they go back and reassess the rigor in the light of that. Then they pretend that they learned from the rigorous exposition. No, they didn't.
It is totally fine to iterate. Learn non-rigorously. Go back to it and iterate on rigor later. As it becomes necessary, and if it ever becomes necessary for your field.
> Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall
Particularly if you are learning from "rigorous" material. But then you go watch some YouTube videos to make up for the absence of didactics in your textbook.
I mean, why don't we just throw Bourbaki books at freshmen and let them sort it out without classes? They are maximally rigorous, therefore maximally great to learn from, right?
So I'm not sure your argument of "out of order" is accurate. The order is what we make. There's no clear optimal way to teach math. Your argument hinges on that. You might argue that the current status quo is working, so why disrupt it, and I'll point around asking if you really think it's so effective when many demonstrate a lack of understanding all around us. That so many struggle with calculus is evidence itself. We need not even acknowledge that there are many children who learn this (and let's certainly not admit that it's far more common for them to learn it in unconventional ways).
To suggest I'm arguing for the elimination of educators is beyond silly. I'd hope the caliber of your arguments would match that of your diction.The Bourbaki group was reponsible for the Mathématiques modernes movement which intended to reform basic education on rigorous math. This may be the world's best documented educational failure in history. It was tried in several countries, so the sample size isn't one. All evidence points at rigor as a terrible educational tool.
The point of Math education isn't to create a clone army of the most pedantic pure Mathematicians in Academia.
> if you really think it's so effective when many demonstrate a lack of understanding all around us. That so many struggle with calculus is evidence itself
Because the first attempt went so well.
New Maths often called a failure but there's not real clear evidence that's the case. This is especially true in America where criticism was quite high as parents were quite vocal and struggled to help their kids (remind you of a different movement?).
There is a certain irony with that too. The major criticisms were about the de-emphasis of arithmetic, arguing that this is the skill people need more. Here we are today though, where everyone has a calculator in their pocket. Plus, people still struggle with extremely basic arithmetic such as calculating a 10% tip... SAT scores are commonly pointed to as evidence, but in the same period of time Verbal skills fell even more[0]! Would you suggest that New Maths was so bad that it made people worse at English? Or maybe there's another explanation like how the number of SAT takers dramatically increased, especially from those in the bottom percentile of high school[1,2].
If you explore the NAEP data[2] there's no decline and there's been progress the entire time for math scores for ages 9, 13, and 17 (the ages that participated).
The Russians famously did very well too.
It would be even a greater irony if we concluded something was a failure because we made mathematical errors in analyzing...
[0] https://www.reddit.com/r/dataisbeautiful/comments/xg6gsz/his...
[1] The Sandia Report and U.S. Achievement: An Assessment: https://www.jstor.org/stable/pdf/27541911.pdf
[2] https://www.nationsreportcard.gov/ndecore/xplore/ltt [2] https://www.reddit.com/r/dataisbeautiful/comments/qz3the/us_...
Just a couple of corrections.
Let's take the Fundamental Theorem of Calculus as an example[0]:
This isn't the Fundamental Theorem of Calculus, it's the usual definition of the derivative of a function of a single real variable. The Fundamental Theorem of Calculus establishes the inverse relationship between differentiation and integration [0].
Unless you're Ramanujan, every mathematician has spent hours banging their head against a literal or metaphorical wall (or both!)
Ramanujan was no stranger to banging his head against the wall. My impression from Kanigel's The Man Who Knew Infinity is that his work ethic and mathematical fortitude were as astonishing as his creativity. For much of his career, he couldn't afford paper in quantity and did his hard work on stone slate, only recording the results. This could make it seem like his results were a product of pure inspiration because he left no trace of the furious activity and struggle that was involved.
From The Man Who Knew Infinity:
When he thought hard, his face scrunched up, his eyes narrowed into a squint. When he figured something out, he sometimes seemed to talk to himself, smile, shake his head with pleasure. When he made a mistake, too impatient to lay down his slate pencil, he twisted his forearm toward his body in a single fluid motion and used his elbow, now aimed at the slate, as an eraser. Ramanujan's was no cool, steady Intelligence, solemnly applied to the problem at hand; he was all energy, animation, force.
[0] https://en.wikipedia.org/wiki/Fundamental_theorem_of_calculu...
Not necessarily proof-heavy, but at least with formally rigorous definitions and theorems.
I agree with this. But I don't see the students rejecting this, but the education degreed peoples who choose texts and the publishers want to make all learning for all people. This is foolish. Most people don't need to know calculus. And if you do learn it, do so with rigor so you actually learn it and not just the appearance of it, which is much much worse.
> Most people don't need to know calculus.
People should have at the minimum a conceptual idea of Calculus. A good motivation is Everyday Calculus: Discovering the Hidden Math All around Us by Oscar E. Fernandez - https://press.princeton.edu/books/paperback/9780691175751/ev...
> And if you do learn it, do so with rigor so you actually learn it
This is not strictly necessary for everybody. The conceptual ideas are what are important; else you are merely doing "plug-and-chug" Maths without any understanding. You need to focus on rigor only based on your needs and at your own pace. Concepts come first Formalism comes second.
A good example; In the Principia Newton actually uses the phrase Quantity of Motion for what we define today as Momentum. The phrase is evocative and beautifully captures the main concept instead of the bland p = m x v definition which though correct and needed for calculations conveys no mental imagery.
In Mathematics one should always approach a concept/idea from multiple perspectives including (but not limited to) Imagination, Conceptual, Graphical, Symbolic, Relationship, Applications, Definition/Theorem/Proof.
Thank you for the book link! One major problem I always had with calculus was that we didn't focus nearly enough on applications of it, outside of some optimization problems, which I loved.
I originally went for engineering, and took cal I and II, then switched to cs and poof all of the math heavy stuff vanished (except maybe some LA for graphics)
Not sure I agree with 'appearance [...] is much worse'.
Given the choice between a class room of first years who believe (in themselves and) an appearance of calculus knowledge or a room of scared undergrads that recoil from any calculus-inspired argument they 'have never learnt it properly', I'll take the former. I can work with that much more easily. Sure, some things might break - but what's the worst that can happen?
We'll sort out the rigour later while we patch the bruises of overextending some analogies.
Most people don't need to know how to read. Most people don't need to know how to add. Most people don't need to know how to use a computer. The foolishness of these statements are all subjective and based on what one believes one "needs". Yet, I have no doubt all of these things can improve peoples lives.
I'd argue the same with calculus. While I don't compute derivatives and integrals every day[0], I certainly use calculus every day. That likely sounds weird, but it is only because one thinks that math and computation is the same. When I drive I use calculus as I'm thinking about my rates of change, not only my velocity. Understanding different easing functions[1] I am able to create a smoother ride, be safer, drive faster, and save fuel. All at the same time!
The magic of the rigor is often lost, but the magic is abstraction. That's what we've done here with the car example. I don't need to compute numbers to "do math", I only need to have an abstract formulation. To understand that multiple variables are involved and there are relationships between them, and understanding that there are concepts like a rate of change, the rate of change of the rate of change, and even the rate of change of the rate of change of the rate of change! (the jerk!)[2].
That's still math. It may not be as rigorous, but a rigorous foundation gives you a greater ability to be less rigorous at times and take advantage of the lessons.
So yes, most people "don't need calculus" but learning it can give them a lot of power in how to think. This is true for much of mathematics. You may argue that this is not how it is taught, but with that I'll agree. The inefficiency of how it is taught is orthogonal to the utility of its lessons.
[0] Is a physicist not doing math just when they do symbol manipulation? I can tell you with great confidence, and experience, that much of their job is doing math without the use of numbers. It is about deriving formulations. Relationship!
[1] https://easings.net/
[2] https://en.wikipedia.org/wiki/Jerk_%28physics%29
I get the argument you're making but that's a bit like saying cavemen used to do calculus as they hunt, which is a valid way of looking at this maybe but they didn't really "use calculus" just intuition. Simillarly, when learning calculus, most people do not do so at a driving course, they do it in the classroom.
If you're willing to stretch the definition of what "using" maths is then it can apply to everything and that devalues the concept as a whole. I'm not on the toilet, I'm doing calculus!
I understand that interpretation but it's different from what I meant.
The difference may be in two different cavemen. One throws his spear on intuition alone. The other is thinking about the speed he throws, how the animal moves, the wind, and so on. There is a formulation, though not as robust as you'd see in a physics book.
In a sense yes.Math is a language, or more accurately a class of languages. If you're formulating your toilet activities, then it might be math. But as you might gather, there's nuance here.
I quoted Poincaré in another comment but I'll repeat here as I think it may help reduce confusion (though may add more)
Or as the category people say "the study of dots and arrows". Anything can be a dot, but you need the arrowsYeah, I do understand your point of view. I'm just doubting if it applies universally, like you may superimpose that assumption on the thinking caveman, but is the thinking caveman really doing the same?
Yes, technique is one thing, but being really good at throwing spears doesn't make you really good at math, is my argument. And most people will encounter maths in a formal setting while lacking the broader perspective that everything is technically "math".
Yet, we need to see the argument from the common person's view, if we're talking about calculus and learning in the traditional sense. The view you stated is quite esoteric and doesn't generalize well in this setting imo.
It's like a musician saying they see music in every action, but to most non-musicians (even if the stated thing is kind of true) that doesn't make a lot of sense etc.
The musician, like the mathematician, understands that every sound is musical. If you want to see this in action it's quite enlightening[0]. I'm glad you brought up that comparison because I think it can help you understand what I really mean. There is depth here. Every human has access to the sounds but the training is needed to put them together and make these formulations. Benn here isn't exactly being formal writing his music using a keyboard and formalizing it down to musical notes on a sheet (though this is something I know he is capable of).
But maybe I should have quoted Picasso instead of Poincaré
His abstract nature to a novice looks like something they could do (Jackson Pollocks is a common example) but he would have told you he couldn't have done this without first mastery of the formal art first.I know this is confusing and I wish I could explain it better. But at least we can see that regardless of the field of expertise we find similar trains of thought. Maybe a bridge can be created by leveraging your own domain of expertise
Maybe I can put it this way: gibberish is more intelligible when crafted by someone who can already speak.
[0] https://m.youtube.com/shorts/ZLPCGEbHoDI
If you care about getting all the nitty gritty details of a "rigorous" proof, maybe the quicker approach is to install Lean on your computer and step through a machine-checked proof from Mathlib. What you get from even the most heavyweight math books is still quite far from showing you all the steps involved.
Nope, but mathematics research is one of the most rarefied fields being extremely difficlt to get into, hard to get money, etc. -- (this is my understanding, at least). Progress is made here by people who, aged 10 are already showing signs of capability.
There's not much need for a large amount of PhD places, and funding, for pure mathematics research.
Likewise, on the applied side, "calculus" now as a pure thing has been dead alone time. Gradients are computed with algorithms and numerical approximations, that are better taught -- with the formal stuff maintained via intuition.
I'm much more open to the idea that the west has this wrong, and we should be more focused on developing the applied side after spending the last century overly focused on the pure
While world class, Russian mathematics is not known for rigor, formality, or detail, so I'm dubious.
There's an old blog that addresses this topic:
https://professorconfess.blogspot.com/
It correlates student loans with the destruction of academic integrity. The idea is school administrators want to capture as many student loan dollars as possible, and that means maximizing the number of enrolled students. To that end, complexity, rigor and difficulty are all reduced as much as possible. Students are prevented from failing, since if they fail they might drop out, reducing profits. I even remember one article which draws comparisons with russian education.
So far, I've only had a brief look at this book and what I've seen I like very much.
Many of us—especially those of us who aren't mathematically gifted—learn mathematics in ways that mostly involve procedures, rules and mechanical manipulation rather than through a rigorous step-by-step theoretical framework (well, anyway that's how I leaned the subject).
Somehow I absorbed those foundations more by osmosis than though a full understanding as my early teachers were more concerned with bashing the basics into my head. Sure, later on when confronted with advanced topics I was forced into more rigorous thinking but it wasn't uniform across the whole field.
What I really like about this book is that it confronts people like me who've already learned mathematics to a reasonably advanced level to review those fundamental concepts. The subject of 'What is Calculus?' doesn't start until Chapter 6, p223, and 'Differentiation' at Ch 8, p261. Those first 200 or so pages not only provide a comprehensive and clearly explained overview of those basic fundamentals but they ensure the reader has good understanding of them before the main subject is introduced.
I'd highly recommend this book either as a refresher or as an adjunct to one's current learning.
Seems like a lot of different audiences. My observation is this is trying to cover 2 of the 3 common tracks:
1 - Proof based calculus for math majors
2 - Technique based calculus for hard science majors
3 - Watered down calculus for soft science and business majors (yes, there are a few schools that are exceptions to this)
If he can pull off unifying 1 and 2, good for him!
I don't think they are unifiable, the aims and methods one needs to learn are just too different. Limits of covering boxes and scaling your epsilons and so on, stuff from Tao's class on analysis is far away from being able to deal either non-trivial differential equations or stability analysis. You can prove all sorts of things about dense subspaces of Hilbert space and still get totally lost in multiple scale analysis, and vice versa. (Ed: epsilon was spelled espikon)
When I saw it was for computer scientists, I briefly hoped that it would take the Big-O, little-o approach as Knuth recommended in 1998. See https://micromath.wordpress.com/2008/04/14/donald-knuth-calc... for a repost of Knuth's letter on the topic.
Sadly, no. It just seems to start with a gentle version of real analysis, leading into basic Calculus.
Related to your comment, not the original post/book:
- On Knuth’s idea (which seems good to me), see http://quomodocumque.wordpress.com/2012/05/29/knuth-big-o-ca... but also the last two comments by David Speyer.
- And see also http://cornellmath.wordpress.com/2007/08/28/non-nonstandard-... and http://texnicalstuff.blogspot.in/2011/05/big-o-notation-for-... that seem to have tried teaching along somewhat similar (but different) lines.
- See https://terrytao.wordpress.com/2022/05/10/partially-specifie... for a further formalization of O notation.
(These links via comments I left to myself at https://shreevatsa.wordpress.com/2014/03/13/big-o-notation-a...)
The book does introduce/use O-notation under the section "Order of Vanishing" in the "Limits and Continuity" chapter.
Honest question: what kind of rigor and abstraction can help us apply maths to solve problems? Don't get me wrong: I enjoy studying abstract maths and was pretty good at it in school. It's just that when it comes to what to study to make one a more effective problem solver in engineering, I was wonder I can best allocate time. For instance, I find studying probability models more helpful than studying the measure theory when it comes to applied data science or statistics. I also find studying books like Mathematical Methods for Physics and Engineering, which focuses a lot more on intuition and applications than rigor, is more effective for me than going pure math books.
Get Zenlisp running too https://www.t3x.org/zsp/index.html and just have a look on how the (intersection) function it's defined.
Now you'll get things in a much easier way, for both programming and math.
That's a pretty diverse audience. Is this .pdf supposed to be a one-size-fits-all effort?
I'm probably dating myself, but at my college, there was one calculus course for everybody. But also, a lot of the students in those areas had overlapping or double majors. For instance I majored in math and physics.
Perhaps the bigger question is whether it's at the right level of difficulty for the audience.
I think there are usually two: Calculus for scientists and engineers which is analytical and has lots of symbols, and Calculus for everyone else which is more practical.
Math majors might have their own. I also know they end up taking complex Calculus.
Thinking about it, ours was a small college -- 2500 students. So there may have been a practical reason for everybody taking the same math courses. They were taught more as "service" courses for the sciences and engineering than as theoretical math courses. And the students who didn't need calculus typically satisfied their math requirement with a statistics course.
Complex analysis and real analysis were among the higher-level courses, attended mostly by math majors, with the proviso that there were a lot of double majors. That was where it got interesting.
The requirements for the physics major were only a handful of math credits shy of the math major.
>The requirements for the physics major were only a handful of math credits shy of the math major.
lol, that's how I ended up with a math major. Got lost in the physics (realized I had no intuition for what was actually happening, just manipulating equations) took a couple extra courses, and boom! Math!
Usually engineering/math calc and then a much less rigorous business/arts&crafts calc for the rest.
> Die Mathematiker sind eine Art Franzosen: Redet man zu ihnen, so übersetzen sie es in ihre Sprache, und alsbald ist es etwas ganz anderes. (Goethe)
Without minimizing the quality or your book, I actually like subject matter books that encompass prerequisite knowledge into the text without forcing the reader to read another book in parallel (e.g. Calculus for Machine Learning by Jason Brownlee or No Bullshit Guide to Math & Physics by Ivan Savov). Though not saying that these books are better, they appeal to my learning style a bit more. Learning institutions tend to force students to take too many courses in parallel when they should find a way to join the subjects, whenever possible, without having to break the instruction into multiple semesters, just to sell more books.
This one is a hard pass. The book needs tighter editing and more rigorous reviewing.
It tries to serve all at once, but ends up in an awkward middle ground. Not deep enough to function as a real analysis text for Mathematicians, yet full of proofs that Scientists and Engineers do not care about, while failing to deliver the kind of practical rigor, those groups need when using calculus as a tool.
Agreed.
I really appreciate author’s effort and for releasing the PDF to the public. There are however areas I think could be made more helpful.
In the chapter on Trigonometric Functions, it begins with discussion of the derivative of the exponential function is itself, and then moves on to define sine and cosine via second degree derivatives. While interesting, this may not be the most helpful approach for intended readers.
The following chapter on Taylor Series also starts with a long discussion about the value of e. It is interesting, but it can feel a bit distracted from the main topic. The treatment of Taylor polynomials might benefit from a different approach similar to other texts.
I used LLM to rewrite above comment to make it sounds less negative. Then I read those two chapters again. This book adds complexities to simple concepts. There are good math books for non-math majors, but this isn't one of them.
Thanks for the pdf. I am more in numeric but this pdf is a nice reference for things complete unreadably on Wikipedia.
Book looks like it could be AI generated, nothing remarkable.
Is there a hard copy to purchase? I can’t seem to find it anywhere.
How much math skills do you need to appreciate this book?
the Postscript at the end says:
While not every student is expected to read the book sequen- tially cover to cover, it is important to have the details in one place. Calculus is not a subject that can be learned in one pass. Indeed, this book nearly assumes readers have already had a year of calculus, as had the students of MAT 157Y. I hope this book will grow with its readers, remaining both readable and informative over multiple traversals, and that it provides a useful bridge between current calculus texts and more advanced real analysis texts.
My first impression, paging through it, is that it's at a somewhat higher level than the typical college calculus course.
What about the Stanford Math 51 book?
>Calculus is an important part of the intellectual tradition handed down to us by the Ancient Greeks.
No it isn't? It was discovered by Newton and Leibnitz. If they're talking about Archimedes and integrals, I seem to recall his work on that was only rediscovered through a palimpsest in the last couple of decades and it contributed nothing towards Newton and Leibnitz's work.
Calculus was actually pioneered by the Kerala School of mathematicians in India during the European Middle Ages, several centuries prior to Newton and Leibniz popularizing it in Europe. The Indian texts were also quite well known to Europeans by that time, it was nowhere close to an independent discovery.
From [0] (emphasis mine):
"Bhāskara II (c. 1114–1185) was acquainted with some ideas of differential calculus and suggested that the "differential coefficient" vanishes at an extremum value of the function.[18] In his astronomical work, he gave a procedure that looked like a precursor to infinitesimal methods. [...] In the 14th century, Indian mathematicians gave a non-rigorous method, resembling differentiation, applicable to some trigonometric functions. Madhava of Sangamagrama and the Kerala School of Astronomy and Mathematics stated components of calculus. They studied series equivalent to the Maclaurin expansions of [redacted] more than two hundred years before their introduction in Europe. [...] however, were not able to 'combine many differing ideas under the two unifying themes of the derivative and the integral, show the connection between the two, and turn calculus into the great problem-solving tool we have today.'"
[0] https://en.wikipedia.org/wiki/Calculus
Archimedes had functionally developed a method of integration (which was how he obtained results like volume/surface area of a sphere, or centre of mass of a hemisphere) in a manuscript that got lost to time and then rediscovered in a palimpsest (pasted and written over with a religious text)
From [0]:
"Laying the foundations for integral calculus and foreshadowing the concept of the limit, ancient Greek mathematician Eudoxus of Cnidus (c. 390–337 BC) developed the method of exhaustion to prove the formulas for cone and pyramid volumes.
"During the Hellenistic period, this method was further developed by Archimedes (c. 287 – c. 212 BC), who combined it with a concept of the indivisibles—a precursor to infinitesimals—allowing him to solve several problems now treated by integral calculus. In 'The Method of Mechanical Theorems' he describes, for example, calculating the center of gravity of a solid hemisphere, the center of gravity of a frustum of a circular paraboloid, and the area of a region bounded by a parabola and one of its secant lines."
[0] https://en.wikipedia.org/wiki/Calculus