Calculus
Chapter 8

Limits and the definition of derivatives

What are limits? How are they defined? How are they used to define the derivative?

May 4, 2017
Lesson by Grant Sanderson
Text adaptation by Kurt Bruns

Calculus is all about making curvy things look straight

Anonymous Professor

The last several lessons have been about the idea of a derivative, and before moving on to integrals, I want to take some time to talk about limits.

To be honest, the idea of a limit is not really anything new. If you know what the word "approach" means you pretty much already know what a limit is, you could say the rest is a matter of assigning fancy notation to the intuitive idea of one value that just gets closer to another. But there are a number of reasons to dive deeper into this topic.

For one thing it's worth showing is how the way I've been describing derivatives so far lines up with the the formal definition of a derivative as it's typically presented in most courses and textbooks. I want to give you a little confidence that thinking of terms like dx and df as concrete non-zero nudges is not just some trick for building intuition; it's actually backed up by the formal definition of a derivative in all of its rigor.

Formal Definition of the derivative

Let's take a look at the formal definition of the derivative. As a reminder, when you have some function f(x), to think about the derivative at a particular input, maybe x=2, you start by imagining nudging that input by some tiny dx, and looking at the resulting change to the output, df.

Image

The ratio df/dx, which can nicely be thought of as the rise-over-run slope between the starting point on the graph and the nudged point, is almost what the derivative is. The actual derivative is whatever this ratio approaches as dx approaches 0.

Image

Just to spell out what is meant here, that nudge to the output "df" is is the difference between f at the starting-input plus dx and f at the starting-input; the change to the output caused by the nudge dx.

Image

To express that you want to find what this ratio approaches as dx approaches 0, you write "lim", for limit, with "dx arrow 0" below it.

Image

Now, you'll almost never see terms with a lowercase d, like dx, inside a limit like this. Instead the standard is to use a different variable, like \Delta x (delta x), or commonly "h" for some reason.

Image

The way I like to think of it is that terms with this lowercase d in the typical derivative expression have built into them the idea of a limit, the idea that dx is supposed to eventually approach 0.

Image

So in a sense this lefthand side "df/dx", the ratio we've been thinking about in the past lessons, is just shorthand for what the righthand side spells out in more detail, writing out exactly what we mean by df, and writing out this limit process explicitly. And that righthand side is the formal definition of a derivative, as you'd commonly see it in any calculus textbook.

Image

The formal derivative definition. Notice that nothing about this definition references the idea of an "infinitely small" change.

No infinitely small rant

Now, if you'll pardon me for a small rant here, I want to emphasize that nothing about this righthand side references the paradoxical idea of an "infinitely small" change. The point of limits is to avoid that.

This value h is the exact same thing as the "dx" I've been referencing throughout the series. It's a nudge to the input of f with some non-zero, finitely small size, like 0.001, that we're analyzing for arbitrarily small choices of h. In fact, the reason people introduce a new variable name into this formal definition, rather than just using dx, is to be clear that these changes to the input are ordinary numbers that have nothing to do with infinitesimals.

Rather than interpret dx as an "infinitely small change", as others like to do, I think you can and should interpret dx as a concrete, finitely small nudge, just so long as you remember to ask what happens as it approaches 0. This method helps build a stronger intuition for where the rules of calculus come from and, more than that, it's not just some trick for building intuitions. Everything I've been saying about derivatives with this concrete-finitely-small-nudge philosophy is a translation of the formal definition of derivatives.

Long story short, the big fuss about limits is that they let us avoid talking about infinitely small changes by instead asking what happens as the size of some change to our variable approaches 0.

Why we care

So why do we teach the limit notation and how does it help us formalize what it means for one value to approach another?

Maybe you are convinced that, on an intuitive level, the language and tools we have invented so far give us what we need to solve these types of problems. When thinking about small nudges to a function's input, as long as we imagine that nudge approaching zero, things usually work out. In the same way, we can zoom in on a point on a curve and convince ourselves that if we zoom in far enough the curve really starts to look straight.

Image

Zoom in on the exponential function e^x at x=0 and the rate of change (slope) starts to look a whole lot like 1.

But, you may still have doubts and questions, as certainly some of the creators of calculus did. For example, just how far do we have to zoom in on a point before a function starts to look like its tangent line at that point?

If you are applying calculus, your primary concern is probably the accuracy of the approximation and you might play a cat and mouse game to choose a small enough dx so that the approximation is is accurate enough to calculate a useful result. A mathematician, on the other hand, is playing a different game; they are interested in whether they can rig the cat and mouse game of choosing smaller and smaller values and getting a more accurate result so that they will always win.

Even more than this, mathematicians care about ensuring all their statements have a precise and airtight meaning, which does not rest on visual intuition. As sensible as it might seem to say that this ratio approaches a certain value, and to draw a line through the graph whose slope approaches that of a tangent line, those seeking rigor insist on something better. In the next chapter, we'll take a look the epsilon-delta definition of limits, which finally puts this idea of "approaching" onto a firm foundation.

Previous Lesson
Implicit differentiation, what's going on here?
Next Lesson
(ε, δ) "epsilon delta" definitions of limits


Thanks

Special thanks to those below for supporting this lesson.

Ali Yahya
Meshal Alshammari
CrypticSwarm
Kaustuv DeBiswas
Kathryn Schmiedicke
Nathan Pellegrin
Karan Bhargava
Justin Helps
Ankit Agarwal
Yu Jun
Dave Nicponski
Damion Kistler
Juan Benet
Othman Alikha
Markus Persson
Dan Buchoff
Derek Dai
Joseph John Cox
Luc Ritchie
Mustafa Mahdi
Daan Smedinga
Jonathan Eppele
Albert Villeneuve Nguyen
Nils Schneider
Mathew Bramson
Jerry Ling
Mark Govea
Vecht
世珉 匡
Rish Kundalia
Achille Brighton
Ripta Pasay
Felipe D
Soufiane KHIAT
dim85
Chris
Chris Willis
Donald Price
Jim Lauridson
Jim Mussared
Gabriel Cunha
Pedro F Pardo
Loro Lukic
David Wyrick
Rahul Suresh
Lee Burnette
John C. Vesey
Patrik Agné
Alvin Khaled
ScienceVR
Michael Rabadi
Alexander Juda
Mads Elvheim
Joseph Cutler
Curtis Mitchell
Andy Petsch
Otavio Good
Viesulas Sliupas
Brendan Shah
Andrew Mcnab
Matt Parlmer
Dan Davison
Jose Oscar Mur-Miranda
Aidan Boneham
Henry Reich
Sean Bibby
Paul Constantine
Justin Clark
Mohannad Elhamod
Ben Granger
Jeffrey Herman