🧮 Brain Teaser

The Monotone Function That Isn't

Let f:[0,1]→Rf: [0,1] \to \mathbb{R} be a function that is differentiable everywhere on [0,1][0,1], with f′(x)≥0f'(x) \geq 0 for all x∈[0,1]x \in [0,1].

Must ff be monotone (non-decreasing)?

Now suppose instead we only know that f′(x)>0f'(x) > 0 for all x∈[0,1]x \in [0,1].

Must ff be strictly increasing?

For each case, either prove it or give a counterexample.

mean value theoremmonotonicitydifferentiabilityreal analysiscounterexample

Answer: The Monotone Function That Isn't

Key Idea / Intuition

The two cases have surprisingly different answers. When f′≥0f' \geq 0 everywhere, the Mean Value Theorem forces ff to be non-decreasing — you cannot go down without having a negative derivative somewhere. When f′>0f' > 0 everywhere, you might expect strict monotonicity, and indeed this is true too, but the subtlety is that "strictly positive derivative everywhere" is stronger than it sounds: there is no room for f(a)=f(b)f(a) = f(b) with a<ba < b, since the MVT would force f′=0f' = 0 somewhere in between.

But here is the real conceptual trap: can a function be everywhere differentiable with f′(x)>0f'(x) > 0 for all xx, yet fail to be strictly increasing globally? The answer is no — but the proof requires care. The interesting "near-miss" is that we can construct functions where f′f' is positive but arbitrarily small (approaching zero), which are still strictly increasing, just not uniformly so.


Formal Proof / Solution

Case 1: f′≥0f' \geq 0 implies ff is non-decreasing

Claim: Yes, ff must be non-decreasing.

Proof: Take any a<ba < b in [0,1][0,1]. By the Mean Value Theorem, there exists c∈(a,b)c \in (a,b) such that f(b)−f(a)=f′(c)(b−a).f(b) - f(a) = f'(c)(b - a). Since f′(c)≥0f'(c) \geq 0 and b−a>0b - a > 0, we get f(b)−f(a)≥0f(b) - f(a) \geq 0, i.e., f(b)≥f(a)f(b) \geq f(a).

So ff is non-decreasing. □\square


Case 2: f′>0f' > 0 implies ff is strictly increasing

Claim: Yes, ff must be strictly increasing.

Proof: Take any a<ba < b in [0,1][0,1]. By the same MVT argument: f(b)−f(a)=f′(c)(b−a)f(b) - f(a) = f'(c)(b-a) for some c∈(a,b)c \in (a,b). Now f′(c)>0f'(c) > 0 and b−a>0b - a > 0, so f(b)−f(a)>0f(b) - f(a) > 0.

Hence ff is strictly increasing. □\square


The Punchline and Subtlety

Both claims are true, and the proofs are almost identical. So where is the interesting mathematics?

The subtlety lives in the converse direction. Consider:

A strictly increasing, differentiable function can have f′(x)=0f'(x) = 0 at some points.

A famous example: f(x)=x3f(x) = x^3 is strictly increasing on R\mathbb{R}, but f′(0)=0f'(0) = 0.

More dramatically, one can construct a strictly increasing C∞C^\infty function whose derivative vanishes on a Cantor set of positive measure — so f′=0f' = 0 on a fat set, yet ff is still strictly increasing!

So the logical structure is: f′>0  ⟹  f strictly increasingf' > 0 \implies f \text{ strictly increasing} f strictly increasing̸  ⟹  f′>0f \text{ strictly increasing} \not\implies f' > 0 f′≥0  ⟹  f non-decreasingf' \geq 0 \implies f \text{ non-decreasing} f non-decreasing̸  ⟹  f′≥0 (it may not even be differentiable)f \text{ non-decreasing} \not\implies f' \geq 0 \text{ (it may not even be differentiable)}

The deeper lesson: positivity of the derivative is a sufficient but not necessary condition for monotonicity, and the MVT is the clean bridge between the local (derivative) and the global (monotone behavior).

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