Mathematics · Advanced · 40 min · Chapter 15 of 28
Real analysis
The calculus, rebuilt on definitions. Limits, completeness of the reals, continuity, and what a derivative really is.
Read first: The language of proof, Differential calculus, Integral calculus
The idea
Analysis is what you get when you refuse to say “approaches” without a definition. A sequence (aₙ) converges to L if for every ε > 0 there exists an integer N such that n > N implies |aₙ − L| < ε. The quantifier order is the whole content: you must answer every tolerance, and you may use a later starting index for a tighter tolerance. A limit of a function is the same idea with x → a instead of n → ∞, and with x ≠ a so the value f(a) is irrelevant.
The rational numbers have holes. The set of rationals whose square is less than 2 is bounded above and has no least upper bound inside the rationals. The real numbers are defined, or axiomatized, so that every nonempty set bounded above has a least upper bound. From that single completeness axiom you get that monotone bounded sequences converge, that Cauchy sequences converge, and that the intermediate value theorem is true. Without it, calculus is a collection of formal tricks that sometimes fail.
f is continuous at a if for every ε > 0 there exists δ > 0 such that |x − a| < δ implies |f(x) − f(a)| < ε. Uniform continuity demands one δ that works for the whole domain, for a given ε. On a closed bounded interval every continuous function is uniformly continuous, attains its bounds, and is Riemann integrable. The mean value theorem says that between a and b there is a point where the instantaneous rate equals the average rate. It is the bridge from local information, the derivative, to global information, the function.
Hold onto this
- A sequence converges to L when the terms eventually stay as close to L as anyone demands.
- The real numbers are complete: every nonempty set that is bounded above has a least upper bound.
- Continuity at a point is an ε–δ statement about inputs controlling outputs.
- On a closed bounded interval, a continuous function attains its maximum and its minimum.
Formulas
Limit of a sequence
The definition of aₙ → L. Every tolerance ε is eventually met and stays met.
- ε
- A positive tolerance you do not choose; you answer it
- N
- A starting index that may depend on ε
Continuity at a point
Inputs close enough to a force outputs close to f(a).
- δ
- A positive allowance in the input, allowed to depend on ε and on a
Mean value theorem
For f continuous on [a, b] and differentiable on (a, b), some c strictly between a and b has derivative equal to the average slope.
- c
- Some point in the open interval, not one you usually compute
Completeness
Every nonempty set S of reals that is bounded above has a least upper bound in the reals.
- sup S
- Least upper bound of S
Worked examples
1. An ε–N proof
Prove that 1/n → 0.
- Let ε > 0 be given.
- Choose an integer N > 1/ε, which exists by the Archimedean property.
- If n > N, then |1/n − 0| = 1/n < 1/N < ε.
The sequence converges to 0. The N you chose depends on ε, as the definition allows.
2. Continuity of a linear function
Prove that f(x) = 2x is continuous at x = 3.
- You need |2x − 6| < ε whenever |x − 3| is small.
- |2x − 6| = 2|x − 3|.
- Choose δ = ε/2. Then |x − 3| < δ implies |2x − 6| < ε.
Continuous at 3, and the same δ works at every point, so the function is uniformly continuous on the whole line.
Try these
Show that (−1)ⁿ does not converge.
Why is “f is continuous because you can draw it without lifting the pen” not a proof?
Common mistakes
- Writing the quantifiers in the wrong order turns convergence into a different, usually false, statement.
- Boundedness of a sequence does not imply convergence. (−1)ⁿ is the witness.
- Differentiability is strictly stronger than continuity. Continuity does not give you a derivative.