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Module 15 · L12 of 16 ~40 min ⚡ +90 XP available

Recurrence Relations

A reduction formula is a recurrence in disguise: $J_n = f(n) \cdot J_{n-1} + g(n)$, or sometimes $J_n$ in terms of $J_{n-2}$. Today you will derive recurrences for genuinely new integral families ($x^n e^{-x}$, $x^n \ln x$, $(\ln x)^n$), evaluate specific $J_n$ values by descent, and recognise the deep connection between recurrences and the reduction formulae of lesson 11.

Today's hook — Define $J_n = \int_0^1 x^n e^{-x}\,dx$. Before reading on, compute $J_0$ by direct integration. Then use parts (with $u = x^n$, $dv = e^{-x}dx$) to derive a relation linking $J_n$ to $J_{n-1}$. Predict: does the recurrence include a non-vanishing boundary term? Compare with card 05.
0/5QUESTS
01
Recall — your gut answer first
+5 XP warm-up

For $J_n = \int_0^1 x^n e^{-x}\,dx$, evaluate $J_0$ directly. Before checking — apply parts once with $u = x^n$, $dv = e^{-x}dx$. Identify which boundary term survives (and which one vanishes). Sketch your derivation below.

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02
The two moves for recurrence problems
+5 XP to read

Recurrence problems reward two habits. Identify the right parts split: usually the polynomial-style factor ($x^n$ or $(\ln x)^n$) becomes $u$ so that differentiating drops the index. Then track the boundary term carefully — unlike the $[0,\pi/2]$ Wallis case, the boundary may contribute a non-zero constant that appears in the recurrence as $g(n)$.

The differentiate-down read: (1) put the polynomial-style factor on $u$, (2) compute the boundary term — it may not vanish, (3) rearrange the result into the standard form $J_n = f(n)J_{n-1} + g(n)$ or $J_n = f(n)J_{n-2} + g(n)$.

Example: $J_n = \int_0^1 x^n e^{-x}dx \Rightarrow J_n = -e^{-1} + nJ_{n-1}$

Choose u = x^n Parts [uv]≠0? Form J_n=f⋅J_{n-1}+g Descend to base J_0 (or J_1)
$J_n = f(n)\,J_{n-1} + g(n)$
Polynomial on $u$, exponential on $dv$
Putting $x^n$ as $u$ ensures $du = nx^{n-1}dx$ drops the power. Putting $e^{-x}$ (or any easy-to-integrate factor) on $dv$ keeps $v$ tractable. This pairing produces a clean $J_{n-1}$ on the right.
Boundary terms may stay
Unlike the $[0,\pi/2]$ sin integrals, here $[uv]_0^1$ often contributes a non-zero constant (e.g. $-e^{-1}$). That constant becomes the $g(n)$ term in $J_n = f(n)J_{n-1} + g(n)$. Always evaluate it.
Descend to a known base
A recurrence is only useful if you can compute the base case. Always state $J_0$ (or $J_1$) explicitly by direct integration before chaining — examiners check that you started from a known value.
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What you'll master
Know

Key facts

  • A reduction formula is a recurrence on the index $n$ of an integral family
  • For $J_n = \int_0^1 x^n e^{-x}dx$: $J_n = nJ_{n-1} - e^{-1}$
  • For $K_n = \int_0^1 x^n \ln x\,dx$: $K_n = -\tfrac{1}{(n+1)^2}$ (closed form, derived by parts)
  • Base cases are always evaluated directly by elementary integration
Understand

Concepts

  • Why "polynomial as $u$" almost always works in integral recurrences
  • Why the boundary term $[uv]_a^b$ may contribute a $g(n)$ piece
  • How a recurrence with linear $f(n)$ leads to factorial-style closed forms
Can do

Skills

  • Derive a recurrence $J_n = f(n)J_{n-1} + g(n)$ from a definite integral by integration by parts
  • Apply the recurrence repeatedly to evaluate $J_n$ for a specific $n$
  • Recognise the link between Module 15's recurrences and the reduction formulae of lesson 11
04
Key terms
Recurrence relationAn equation expressing the $n$th term of a sequence (here $J_n$) in terms of earlier terms ($J_{n-1}$, $J_{n-2}$, …). For integrals, derived from integration by parts.
Reduction formulaA specific name for an integral recurrence. The two terms are used interchangeably in NESA materials.
Base caseThe smallest-index value ($J_0$ or $J_1$) computed directly by elementary integration. The recurrence is anchored to this value.
Forcing term $g(n)$In $J_n = f(n)J_{n-1} + g(n)$, the $g(n)$ piece (often a constant or simple function of $n$) comes from the boundary term $[uv]_a^b$ when it does not vanish.
Homogeneous recurrenceA recurrence with $g(n) = 0$, e.g. $I_n = \tfrac{n-1}{n}I_{n-2}$. Often produces factorial-style closed forms.
DescentThe repeated application of a recurrence to reduce $J_n$ to $J_0$ or $J_1$. Each step lowers the index by $1$ or $2$ depending on the form.
MEX-C1NESA outcome (Further Integration): derives and applies recurrence relations for definite integrals, evaluates specific $J_n$ by repeated descent.
05
A model recurrence: $J_n = \int_0^1 x^n e^{-x}\,dx$
core concept

Take $u = x^n$, $dv = e^{-x}dx$, so $du = nx^{n-1}dx$ and $v = -e^{-x}$. Then $$J_n = \bigl[-x^n e^{-x}\bigr]_0^1 + n\int_0^1 x^{n-1}e^{-x}\,dx.$$

Evaluate the boundary: at $x = 1$, $-x^n e^{-x} = -e^{-1}$; at $x = 0$, $-x^n e^{-x} = 0$ (provided $n \geq 1$). So $\bigl[-x^n e^{-x}\bigr]_0^1 = -e^{-1}$.

Therefore $\boxed{J_n = nJ_{n-1} - e^{-1}}$ for $n \geq 1$, with $J_0 = \int_0^1 e^{-x}dx = 1 - e^{-1}$.

Worked through the hook. $J_1 = 1 \cdot J_0 - e^{-1} = (1 - e^{-1}) - e^{-1} = 1 - 2e^{-1}$. Then $J_2 = 2J_1 - e^{-1} = 2(1 - 2e^{-1}) - e^{-1} = 2 - 5e^{-1}$. Each step uses the same one-line recurrence.

Recurrence versus reduction. Lesson 11's $I_n = \tfrac{n-1}{n}I_{n-2}$ is a homogeneous recurrence (no forcing term). Today's $J_n = nJ_{n-1} - e^{-1}$ is non-homogeneous: the $-e^{-1}$ piece arises directly from the non-vanishing boundary term. Both are recurrences — the difference is whether the boundary contributes.

Take $u = x^n$, $dv = e^{-x}dx$; the polynomial goes on $u$ to differentiate down · Boundary $\bigl[-x^n e^{-x}\bigr]_0^1 = -e^{-1}$ (only the $x = 1$ end contributes for $n \geq 1$) · Recurrence: $J_n = nJ_{n-1} - e^{-1}$ for $n \geq 1$, with $J_0 = 1 - e^{-1}$ · Non-homogeneous recurrence — the forcing term comes from the surviving boundary value

Pause — copy the recurrence $J_n = nJ_{n-1}-e^{-1}$, its derivation ($u = x^n$, $dv = e^{-x}dx$, boundary $= -e^{-1}$), and the base $J_0 = 1-e^{-1}$ into your book.

Quick check: For $J_n = \int_0^1 x^n e^{-x}dx$ satisfying $J_n = nJ_{n-1} - e^{-1}$ with $J_0 = 1 - e^{-1}$, what is $J_2$?

06
Connection to reduction formulae
core concept

We just saw the model recurrence $J_n = nJ_{n-1} - e^{-1}$ for $J_n = \int_0^1 x^n e^{-x}\,dx$, where the boundary term $-e^{-1}$ (from the $x=1$ end) creates a non-homogeneous forcing term. That raises a question: how does this non-homogeneous recurrence fit the broader framework of reduction formulas? This card answers it → homogeneous recurrences arise when the boundary term vanishes; single-step index drop is typical for $x^n \times$ exponential; two-step drop occurs when a Pythagorean identity is needed.

Every reduction formula from lesson 11 is a recurrence; every integral recurrence in this lesson is a reduction formula. The difference is rhetorical, not mathematical.

  • Homogeneous form $J_n = f(n)J_{n-k} + 0$: arises when the boundary term vanishes (e.g. Wallis integrals on $[0,\pi/2]$).
  • Non-homogeneous form $J_n = f(n)J_{n-k} + g(n)$: arises when the boundary term contributes a non-zero value (e.g. $J_n = nJ_{n-1} - e^{-1}$ above).

Choice between $J_{n-1}$ and $J_{n-2}$ depends on what comes out of the parts identity. Single-step recurrences (involving $J_{n-1}$) are typical when the integrand splits neatly into polynomial $\times$ elementary; two-step recurrences (involving $J_{n-2}$) are typical when a Pythagorean identity must be used to recover the same family on the right.

$$\text{Wallis: } I_n = \tfrac{n-1}{n}I_{n-2} \quad\Longleftrightarrow\quad \text{Gamma-like: } J_n = nJ_{n-1} - e^{-1}$$
Where this leads. The full Gamma integral $\Gamma(n+1) = \int_0^\infty x^n e^{-x}dx = n!$ uses the homogeneous version of today's recurrence (the boundary at $\infty$ vanishes). Restricting to $[0,1]$ keeps the boundary alive — that is the entire structural difference between $n!$ and the lower incomplete Gamma function.

Reduction formula $=$ integral recurrence (same idea) · Homogeneous: boundary term vanishes; non-homogeneous: boundary term contributes $g(n)$ · Single-step ($J_{n-1}$) is typical for $x^n \times$ elementary integrands · Two-step ($J_{n-2}$) is typical when a Pythagorean identity is needed

Pause — copy the homogeneous vs non-homogeneous distinction (boundary vanishes or contributes $g(n)$), the single-step ($J_{n-1}$) vs two-step ($J_{n-2}$) rule, and the Pythagorean-identity trigger for two-step into your book.

Did you get this? True or false: the recurrence $I_n = \tfrac{n-1}{n}I_{n-2}$ for the Wallis integral is homogeneous (i.e., has no forcing term $g(n)$).

PROBLEM 1 · DERIVE A RECURRENCE

Let $J_n = \int_0^1 x^n e^{-x}\,dx$ for $n \geq 1$. Show that $J_n = nJ_{n-1} - e^{-1}$.

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Take $u = x^n$, $dv = e^{-x}\,dx$, so $du = nx^{n-1}\,dx$ and $v = -e^{-x}$.
"Polynomial as $u$, easy-to-integrate factor as $dv$" is the recurrence-builder's default. Differentiating $x^n$ drops the index — which is exactly the engine of the recurrence.
PROBLEM 2 · USE THE RECURRENCE TO EVALUATE $J_3$

Use the recurrence $J_n = nJ_{n-1} - e^{-1}$ with $J_0 = 1 - e^{-1}$ to evaluate $J_3 = \int_0^1 x^3 e^{-x}\,dx$.

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$J_1 = 1 \cdot J_0 - e^{-1} = (1 - e^{-1}) - e^{-1} = 1 - 2e^{-1}$.
Always start with the base case and apply the recurrence once at a time — substituting blindly into a triple chain invites slips with the additive $-e^{-1}$ term.
PROBLEM 3 · TWO-STEP RECURRENCE

Let $L_n = \int_0^1 x^n (1-x)^n\,dx$. Show $L_n = \tfrac{n}{n+1}\cdot L_{n-1}$ is wrong by direct check, then derive the correct relation linking $L_n$ to $L_{n-1}$.

1
Direct: $L_0 = \int_0^1 1\,dx = 1$ and $L_1 = \int_0^1 x(1-x)\,dx = \bigl[\tfrac{x^2}{2} - \tfrac{x^3}{3}\bigr]_0^1 = \tfrac{1}{6}$. The proposed $\tfrac{n}{n+1}L_{n-1}$ with $n = 1$ gives $\tfrac{1}{2}\cdot 1 = \tfrac{1}{2} \neq \tfrac{1}{6}$, so the formula is wrong.
Always test a proposed recurrence against the smallest indices before committing — base-case checks catch a wrong factor instantly.

Fill the gap: For $J_n = \int_0^1 x^n e^{-x}dx$, applying integration by parts with $u = $ gives the recurrence $J_n = nJ_{n-1} + g$, where the forcing term is $g = $ .

Trap 01
Dropping the boundary term
Recurrence problems are not Wallis problems — boundary terms do not automatically vanish. Forgetting the $-e^{-1}$ in $J_n = nJ_{n-1} - e^{-1}$ converts a non-homogeneous recurrence into a homogeneous one and changes every subsequent answer.
Trap 02
Wrong choice of $u$ and $dv$
Putting $e^{-x}$ as $u$ leaves a $\int x^n \cdot (-e^{-x})\,dx$ piece that doesn't reduce — the index never drops. The polynomial factor must go on $u$ so that $du$ lowers the power. Reverse the choice and you lose all forward progress.
Trap 03
Skipping the base case
A recurrence is useless without $J_0$ (or $J_1$). State the base case explicitly by direct integration before chaining — a derivation that leaves $J_0$ unevaluated cannot produce a numerical answer.

Did you get this? True or false: in the recurrence $J_n = nJ_{n-1} - e^{-1}$ for $J_n = \int_0^1 x^n e^{-x}dx$, the term $-e^{-1}$ arises from the boundary $[-x^n e^{-x}]_0^1$ evaluated at $x = 1$.

Work mode · how are you completing this lesson?
1

Use the recurrence $J_n = nJ_{n-1} - e^{-1}$ with $J_0 = 1 - e^{-1}$ to evaluate $J_4$.

2

Let $K_n = \int_1^e (\ln x)^n\,dx$ for $n \geq 1$. Derive the recurrence $K_n = e - nK_{n-1}$ and state $K_0$.

3

Using the recurrence from question 2, evaluate $K_2 = \int_1^e (\ln x)^2\,dx$.

4

For $K_n = \int_0^1 x^n \ln x\,dx$ ($n \geq 0$), use integration by parts to show $K_n = -\tfrac{1}{(n+1)^2}$. (Hint: $u = \ln x$, $dv = x^n dx$. Justify why the boundary at $0$ vanishes.)

5

Connect to lesson 11: rewrite the Wallis recurrence $I_n = \tfrac{n-1}{n}I_{n-2}$ in the standard recurrence form $J_n = f(n)J_{n-k} + g(n)$, identifying $f$, $k$ and $g$.

Odd one out: Three of these recurrences have a vanishing boundary term ($g = 0$). Which one does NOT?

11
Revisit your thinking

Earlier you computed $J_0 = 1 - e^{-1}$ and tracked which boundary term survived when applying parts to $\int_0^1 x^n e^{-x}\,dx$.

The non-vanishing boundary at $x = 1$ is precisely what makes this recurrence non-homogeneous: it contributes the $-e^{-1}$ forcing term in $J_n = nJ_{n-1} - e^{-1}$. Compare with the lesson 11 Wallis case, where the boundary term vanishes at both endpoints and the recurrence is homogeneous. Recognising which type of recurrence you are deriving — homogeneous or non-homogeneous — is the single most useful diagnostic in Module 15.

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01
Multiple choice
+5 XP per correct · +25 XP all-correct

Pick your answer, then rate your confidence — that tells the system what to drill next. Each retry pulls a fresh mix from the bank.

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Short answer
ApplyBand 32 marks

Q1. Given $J_n = nJ_{n-1} - e^{-1}$ with $J_0 = 1 - e^{-1}$, evaluate $J_2 = \int_0^1 x^2 e^{-x}\,dx$. Show each step of the chain. (2 marks)

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ApplyBand 43 marks

Q2. Let $J_n = \int_0^1 x^n e^{-x}\,dx$ for $n \geq 1$. Use integration by parts to derive $J_n = nJ_{n-1} - e^{-1}$. Justify the value of each boundary contribution. (3 marks)

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AnalyseBand 53 marks

Q3. For $K_n = \int_1^e (\ln x)^n\,dx$ with $n \geq 1$, show that $K_n = e - nK_{n-1}$. Hence evaluate $K_3$. (3 marks)

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Comprehensive answers (click to reveal)

Activity answers:

1. $J_1 = 1 - 2e^{-1}$, $J_2 = 2 - 5e^{-1}$, $J_3 = 6 - 16e^{-1}$, $J_4 = 4J_3 - e^{-1} = 24 - 65e^{-1}$.

2. $K_0 = e - 1$. With $u = (\ln x)^n$, $dv = dx$: $K_n = [x(\ln x)^n]_1^e - n\int_1^e (\ln x)^{n-1}dx = e \cdot 1 - 0 - nK_{n-1} = e - nK_{n-1}$.

3. $K_1 = e - 1\cdot(e-1) = 1$; $K_2 = e - 2\cdot 1 = e - 2$.

4. With $u = \ln x$, $dv = x^n dx$: $K_n = \bigl[\tfrac{x^{n+1}\ln x}{n+1}\bigr]_0^1 - \tfrac{1}{n+1}\int_0^1 x^n\,dx = 0 - \tfrac{1}{(n+1)^2} = -\tfrac{1}{(n+1)^2}$. The boundary at $x = 0$ vanishes because $x^{n+1}\ln x \to 0$ as $x \to 0^+$.

5. $f(n) = \tfrac{n-1}{n}$, $k = 2$, $g(n) = 0$ — homogeneous, two-step.

Q1 (2 marks): $J_1 = 1 - 2e^{-1}$ [1]; $J_2 = 2J_1 - e^{-1} = 2 - 5e^{-1}$ [1].

Q2 (3 marks): Parts with $u = x^n$, $dv = e^{-x}dx$ [1]; identify boundary $[-x^n e^{-x}]_0^1$ — at $x = 1$ this is $-e^{-1}$, at $x = 0$ this is $0$ for $n \geq 1$ [1]; the remaining integral is $nJ_{n-1}$, giving $J_n = nJ_{n-1} - e^{-1}$ [1].

Q3 (3 marks): Derivation $K_n = e - nK_{n-1}$ as in activity 2 [1]; $K_0 = e-1$, $K_1 = 1$, $K_2 = e-2$ [1]; $K_3 = e - 3K_2 = e - 3(e-2) = 6 - 2e$ [1].

01
Boss battle · The Recurrence Forger
earn bronze · silver · gold

Five timed questions on deriving and applying integral recurrences. Beat the boss to bank a tier — gold (90% + speed), silver (75%), or bronze (50%). Replays welcome.

⚔ Enter the arena
02
Science Jump · platform challenge

Climb platforms by answering quick recurrence questions. Lighter alternative to the boss.

Mark lesson as complete

Tick when you've finished the practice and review.

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