Mathematical Induction and Recursion
Proving infinitely many statements with two steps, and the recursive definitions that induction is built to reason about.
Leads to: Recursion and induction underlie dynamic programming, tree pricing (Phase 14), and convergence proofs for numerical schemes.
Learning Objectives
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- State and apply the principle of weak induction: base case plus inductive step.
- Use strong induction when the step needs several previous cases.
- Define sequences recursively and connect the definition to an inductive proof of a closed form.
- Implement a recursive computation and validate it against its proved closed form.
Key Vocabulary
- Weak (ordinary) induction
- Prove P(1), then P(k)⇒P(k+1); conclude P(n) for all n≥1.
- Strong induction
- Assume P holds for all values up to k to prove P(k+1); equivalent in power to weak induction.
- Base case
- The smallest instance you verify directly; without it the whole argument collapses.
- Inductive hypothesis
- The assumed truth of P(k) (or all j≤k) used to establish the next case.
- Recursive definition
- A definition of a_n in terms of earlier terms plus explicit initial values.
- Closed form
- A non-recursive formula giving a_n directly from n.
The principle
To prove a statement \(P(n)\) for every natural number, you need only two things: a base case \(P(1)\) and an inductive step \(P(k)\Rightarrow P(k+1)\). Like dominoes: knock the first, and guarantee each knocks the next.
Strong induction
Sometimes \(P(k+1)\) needs more than the single previous case. Strong induction assumes \(P(1),\dots,P(k)\) all hold. It proves, for instance, that every integer \(n\ge 2\) has a prime factorization: either \(n\) is prime, or \(n=ab\) with \(a,b\lt n\), and both factor by the (strong) hypothesis.
Recursion: definitions that call themselves
A recursive definition gives initial terms and a rule producing later ones. The Fibonacci numbers \(F_1=F_2=1,\ F_n=F_{n-1}+F_{n-2}\) are the canonical example. Induction is the natural tool to prove properties of recursively defined objects because the recurrence is an inductive step.
Interactive: recursion meets its closed form
- Skipping or fudging the base case; a valid inductive step with no base proves nothing (you can ‘prove’ all numbers are equal that way).
- Assuming what you want to prove: the inductive hypothesis is P(k), not P(k+1).
- Using weak induction when the step genuinely needs several earlier cases - switch to strong induction.
- Off-by-one errors in the base index (starting at 0 vs 1) that break the chain.
- Always write the base case explicitly and check it - it is where sneaky errors hide.
- State the inductive hypothesis in a labeled line so the reader sees exactly what you assumed.
- If P(k+1) refers to two or more earlier terms (like Fibonacci), reach for strong induction.
- A recurrence you can compute is a free test harness for a closed form you claim to have proved.
Knowledge Check
Practical Exercise
Prove by induction that \(\sum_{i=1}^{n} i^2=\tfrac{n(n+1)(2n+1)}{6}\) for all \(n\ge 1\).
Base. \(n=1\): left side \(=1\), right side \(=\tfrac{1\cdot2\cdot3}{6}=1\). ✓
Step. Assume \(\sum_{i=1}^{k} i^2=\tfrac{k(k+1)(2k+1)}{6}\). Then
which is the formula with \(n=k+1\) (since \(2(k+1)+1=2k+3\)). By induction it holds for all \(n\ge1\). □
Lesson Summary
Formula Sheet Additions
Retrieval Practice
Close the lesson and answer from memory before checking. This is deliberate, effortful recall - the single highest-yield study action.
A: A verified base case and an inductive step P(k)⇒P(k+1); without the base case the chain never starts, so nothing is proved - you can even ‘prove’ false universals.
A: When establishing P(k+1) requires assuming several earlier cases (e.g. n=ab with a,b
Completion Checklist
- I can explain the core ideas in my own words
- I worked the derivations/examples by hand
- I completed the interactive workbench(es)
- I passed the knowledge check
Source References
This lesson synthesizes and paraphrases concepts from the sources below. No copyrighted text, problem sets, or solutions are reproduced. Return to the originals for full depth.
- Calculus, Vol. I (Tom Apostol, 2nd ed., 1967) foundational - Vol. I, I 4.2-4.3 - The induction principle and its use to prove summation formulas and inequalities.
- Make It Stick (Brown, Roediger & McDaniel, 2014) foundational - generation effect - Generation and self-testing: proving then numerically checking a closed form as retrieval practice.