Methods: Chapter 18-21 - Calculus

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23 Terms

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Average Rate of Change

  • Measures how much a function changes on average over an interval

  • Formula: (f(b) - f(a)) / (b - a)

  • It's the gradient of the secant line through (a, f(a)) and (b, f(b))

  • For motion, it's average speed = distance ÷ time

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The Derivative

Key Concepts

  • A secant is a line through two points on a curve.

  • A tangent is a line that touches the curve at one point with the same gradient.

  • The instantaneous rate of change is the gradient of the tangent.

First Principles Definition

  • Derivative: Slope
    f'(x) = lim (h → 0) [(f(x + h) - f(x)) / h]

Approximating Derivatives

  • For small h:
    f'(a) ≈ (f(a + h) - f(a)) / h

Tangents

  • Gradient of tangent at x = a:
    👉 f'(a)
    So at point (1, −2), if f'(1) = −3, the tangent’s slope = -3.

Notes

  • Derivative exists only if the limit exists.

  • All polynomials are differentiable.

<p><strong>Key Concepts</strong></p><ul><li><p class="">A secant is a line through two points on a curve.</p></li><li><p class="">A tangent is a line that touches the curve at one point with the same gradient.</p></li><li><p class="">The instantaneous rate of change is the gradient of the tangent.</p></li></ul><p class=""><strong>First Principles Definition</strong></p><ul><li><p class="">Derivative: Slope <br>f'(x) = lim (h → 0) [(f(x + h) - f(x)) / h]</p></li></ul><p class=""><strong>Approximating Derivatives</strong></p><ul><li><p class="">For small h:<br>f'(a) ≈ (f(a + h) - f(a)) / h</p></li></ul><p class=""><strong>Tangents</strong></p><ul><li><p class="">Gradient of tangent at x = a:<br><span data-name="point_right" data-type="emoji">👉</span> <strong>f'(a)</strong><br>So at point (1, −2), if <strong>f'(1) = −3</strong>, the tangent’s slope = <strong>-3</strong>.</p></li></ul><p class=""><strong>Notes</strong></p><ul><li><p class="">Derivative exists only if the limit exists.</p></li><li><p class="">All polynomials are differentiable.</p></li></ul><p></p>
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Derivative Rule - Basic

Power Rule
If f(x) = xⁿ, then
👉 f'(x) = n xⁿ⁻¹
(Proven using the binomial theorem.)

Special Cases

  • Constant:
    f(x) = c ⇒ f'(x) = 0

  • Linear:
    f(x) = mx + c ⇒ f'(x) = m

Add-Ons

  • Multiply:
    f(x) = k ⋅ g(x) ⇒ f'(x) = k ⋅ g'(x)

  • Sum:
    f = g + h ⇒ f' = g' + h'

  • Difference:
    f = g − h ⇒ f' = g' − h'

🧪 Examples
f(x) = x⁵ − 2x³ + 2
👉 f'(x) = 5x⁴ − 6x²

f(x) = 3x³ − 6x² + 1
👉 f'(x) = 9x² − 12x, so f'(1) = −3

<p><strong>Power Rule</strong><br>If <strong>f(x) = xⁿ</strong>, then<br><span data-name="point_right" data-type="emoji">👉</span> <strong>f'(x) = n xⁿ⁻¹</strong><br>(Proven using the binomial theorem.)</p><p class=""><strong>Special Cases</strong></p><ul><li><p class=""><strong>Constant:</strong><br>f(x) = c ⇒ <strong>f'(x) = 0</strong></p></li><li><p class=""><strong>Linear:</strong><br>f(x) = mx + c ⇒ <strong>f'(x) = m</strong></p></li></ul><p class=""><strong>Add-Ons</strong></p><ul><li><p class=""><strong>Multiply:</strong><br>f(x) = k ⋅ g(x) ⇒ <strong>f'(x) = k ⋅ g'(x)</strong></p></li><li><p class=""><strong>Sum:</strong><br>f = g + h ⇒ <strong>f' = g' + h'</strong></p></li><li><p class=""><strong>Difference:</strong><br>f = g − h ⇒ <strong>f' = g' − h'</strong></p></li></ul><p class=""><span data-name="test_tube" data-type="emoji">🧪</span> <strong>Examples</strong><br>f(x) = x⁵ − 2x³ + 2<br><span data-name="point_right" data-type="emoji">👉</span> <strong>f'(x) = 5x⁴ − 6x²</strong></p><p class="">f(x) = 3x³ − 6x² + 1<br><span data-name="point_right" data-type="emoji">👉</span> <strong>f'(x) = 9x² − 12x</strong>, so <strong>f'(1) = −3</strong></p>
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Lebiniz Notation

If y = x³, write:
👉 dy/dx = 3x²
(Same idea, different style. Don't treat dy/dx like a fraction.)

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Differentiating xⁿ where n is a negative integer

  • Power rule still applies: derivative of xⁿ is nxn-1

  • Domain: x ≠ 0 (no zero allowed because of division)

  • Examples:
     • d/dx (1/x) = -1/x²
     • d/dx (x⁻³) = -3x⁻⁴

  • Constants → derivative is 0

  • Tangent slope = derivative evaluated at point

  • Negative powers = fractional forms, watch domain carefully!

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Differentiating rational powers (x to the p over q)

  • Use first principles for simple powers like x¹ᐟ², x¹ᐟ³

  • Key identity: aⁿ - bⁿ = (a - b)(aⁿ⁻¹ + aⁿ⁻²b + … + bⁿ⁻¹)

  • Use chain rule for general rational powers:
     • If y = xᵖ⁄q, write y = (x¹⁄q)ᵖ
     • Then dy/dx = (p/q) × x^(p/q - 1)

  • Domain: x > 0 (to avoid issues with roots of negatives)

  • Applies to any real non-zero power: derivative of xᵃ is a × xᵃ⁻¹

  • Examples:
     • d/dx (x²ᐟ³) = (2/3) × x⁻¹ᐟ³
     • d/dx (4x²ᐟ³) = 4 × (2/3) × x⁻¹ᐟ³

  • Graphs of fractional powers are smooth for x > 0 but tricky near 0 for some powers

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Chain Rule

  • The chain rule is like mom(son) — a function inside a function.

  • To differentiate y = mom(son), do: derivative = son' × mom'(son).

Break y = f(g(x)) into:

  • Son = g(x) (inner function)

  • Mom = f(u) (outer function, with u = son)

Steps:

  1. Differentiate inner: son' = g'(x)

  2. Differentiate outer at son: mom'(son) = f'(u) at u = g(x)

  3. Multiply: dy/dx = mom'(son) × son'

Example: y = (3x + 4)^20

  • son = 3x + 4, son' = 3

  • mom = u^20, mom' = 20u^19

  • derivative = 20(3x + 4)^19 × 3 = 60(3x + 4)^19

Official formulas:

Chain rule (function notation):
(f ∘ g)'(x) = f'(g(x)) × g'(x)
where (f ∘ g)(x) = f(g(x))

Chain rule (Leibniz notation):
dy/dx = dy/du × du/dx

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Tangents & Normal

  • Derivative gives the gradient of the tangent at any point on a curve.

  • Tangent line equation at (x₁, y₁):
    y − y₁ = f'(x₁)(x − x₁)

  • Normal line is perpendicular to the tangent.

  • If tangent gradient = m, normal gradient = −1/m

Example tangent:
For y = x³ + ½x² at x = 1:

  • Point: (1, 3/2)

  • Gradient: f'(1) = 4

  • Tangent: y − 3/2 = 4(x − 1) → y = 4x − 5/2

Example normal:
For y = x³ − 2x² at (1, −1):

  • Tangent gradient: f'(1) = −1

  • Normal gradient: 1

  • Normal: y + 1 = 1(x − 1) → y = x − 2

<ul><li><p class="">Derivative gives the <strong>gradient of the tangent</strong> at any point on a curve.</p></li><li><p class="">Tangent line equation at (x₁, y₁):<br><strong>y − y₁ = f'(x₁)(x − x₁)</strong></p></li><li><p class="">Normal line is <strong>perpendicular</strong> to the tangent.</p></li><li><p class="">If tangent gradient = <strong>m</strong>, normal gradient = <strong>−1/m</strong></p></li></ul><p class="">Example tangent:<br>For y = x³ + ½x² at x = 1:</p><ul><li><p class="">Point: (1, 3/2)</p></li><li><p class="">Gradient: f'(1) = 4</p></li><li><p class="">Tangent: y − 3/2 = 4(x − 1) → y = 4x − 5/2</p></li></ul><p class="">Example normal:<br>For y = x³ − 2x² at (1, −1):</p><ul><li><p class="">Tangent gradient: f'(1) = −1</p></li><li><p class="">Normal gradient: 1</p></li><li><p class="">Normal: y + 1 = 1(x − 1) → y = x − 2</p></li></ul><p></p>
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Stationary Points

  • A point (a, f(a)) on curve y = f(x) is stationary if the derivative = 0 at x = a.

  • In symbols: f'(a) = 0 or dy/dx = 0 at x = a.

  • At stationary points, the tangent is horizontal (parallel to x-axis).

Types:

  • Local Maximum: f′(x) changes from + to – (peak)

  • Local Minimum: f′(x) changes from – to + (valley)

  • Inflection Point: f′(x)=0, no sign change (flat but no turn)

Turning Points: Local max and min only.

Examples:

  1. y = 9 + 12x − 2x²

    • dy/dx = 12 − 4x

    • Set to 0: 12 − 4x = 0 → x = 3

    • Stationary point: (3, 27)

<ul><li><p class="">A point (a, f(a)) on curve y = f(x) is <strong>stationary</strong> if the <strong>derivative = 0</strong> at x = a.</p></li><li><p class="">In symbols: <strong>f'(a) = 0</strong> or <strong>dy/dx = 0</strong> at x = a.</p></li><li><p class="">At stationary points, the <strong>tangent is horizontal</strong> (parallel to x-axis).</p></li></ul><p class=""><strong>Types:</strong></p><ul><li><p class=""><strong>Local Maximum:</strong> f′(x) changes from + to – (peak)</p></li><li><p class=""><strong>Local Minimum:</strong> f′(x) changes from – to + (valley)</p></li><li><p class=""><strong>Inflection Point:</strong> f′(x)=0, no sign change (flat but no turn)</p></li></ul><p class=""><strong>Turning Points:</strong> Local max and min only.</p><p><strong>Examples:</strong></p><ol><li><p class="">y = 9 + 12x − 2x²</p><ul><li><p class="">dy/dx = 12 − 4x</p></li><li><p class="">Set to 0: 12 − 4x = 0 → x = 3</p></li><li><p class="">Stationary point: (3, 27)</p></li></ul></li></ol><p></p>
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Steps to solve max/min problems

  • Draw & label diagram; define variables and limits.

  • Express quantity to max/min as a single-variable function.

  • Find stationary points where derivative = 0.

  • Test points to identify local max/min/neither.

  • Check function values at domain endpoints if any.

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Second Derivative

The derivative of the first derivative:
f″(x) = d/dx (f′(x))

Example:
If f(x) = 2x² + 4x + 1, then f′(x) = 4x + 4 and f″(x) = 4

In physics:
position = x(t), velocity = dx/dt, acceleration = d²x/dt²

Example:
f(x) = 3x³ + 2x⁻¹ + 1
f′(x) = 9x² − 2x⁻²
f″(x) = 18x + 4x⁻³

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Second Derivative Test

If f ''(x) > 0, the function is concave up ⇒ local minimum
If f ''(x) < 0, the function is concave down ⇒ local maximum
If f ''(x) = 0, the test is inconclusive

Use it at critical points where f '(x) = 0

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Sketching Graphs

Steps for sketching graphs:

  • Find x-axis and y-axis intercepts and stationary points.

  • Identify where the graph is increasing and decreasing.

  • Determine the nature of each stationary point:
    • local maximum
    • local minimum
    • stationary point of inflection

  • Identify vertical asymptotes.

  • Understand the behavior as x → +∞ and x → −∞.

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Graphs of the derivative function

  • Sign of derivative tells slope direction of original graph:

    • If f′(x) > 0, graph slopes up (increasing).

    • If f′(x) < 0, graph slopes down (decreasing).

    • If f′(x) = 0, potential stationary point.

  • Intervals:

    • Increasing where f′(x) > 0.

    • Decreasing where f′(x) < 0.

    • Stationary points where f′(x) = 0.

  • Derivative tests:

    • f′(x) > 0 → function strictly increasing on interval.

    • f′(x) < 0 → function strictly decreasing on interval.

    • But watch out: strictly increasing doesn’t always mean f′(x) > 0 everywhere (like f(x) = x³).

  • Gradient & angle connection:

    • Gradient m = tan(θ), where θ is angle with x-axis.

    • E.g., θ=45° means m=1; θ=135° means m=−1.

  • Use derivative to find tangents at given slopes or angles.

CAS: Plot graph of normal function and derivative function.

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Families of Functions and Transformations

Given f(x) = (x − a)2(x − b), with a, b positive and b > a:

a) Derivative: f'(x) = (x − a)(3x − a − 2b) (found using CAS)
b) Stationary points: (a, 0) and ( (a + 2b)/3 , value from f(x) )
c) Local max at (a, 0) because f'(x) changes from positive to negative around a
d) Given stationary points at x=3 and x=4, then:

  • a = 3

  • (a + 2b)/3 = 4 → b = 9/2

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Limits and Continuity

Limit Definition
Limit (lim): As x approaches a, f(x) gets arbitrarily close to L. Written as lim x→a f(x) = L.

For many functions (especially polynomials), lim x→a f(x) = f(a).

If f is not defined at a, factor or simplify to find the limit.

Algebra of Limits (if limits exist):
lim x→a (f(x) + g(x)) = lim x→a f(x) + lim x→a g(x)
lim x→a (k f(x)) = k lim x→a f(x)
lim x→a (f(x) g(x)) = lim x→a f(x) × lim x→a g(x)
lim x→a (f(x) / g(x)) = (lim x→a f(x)) / (lim x→a g(x)), if lim x→a g(x) ≠ 0.

Left and Right Limits:
lim x→a⁻ f(x) is the limit approaching from the left.
lim x→a⁺ f(x) is the limit approaching from the right.

Limit exists only if both are equal.

Continuity at x = a:
f is continuous at a if:

  • f(a) is defined, and

  • lim x→a f(x) = f(a).

Otherwise, f is discontinuous at a.

Note:
Polynomials are continuous everywhere.

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When is a function differentiable?

When is a function differentiable?

  • A function f is differentiable at x = a if the limit of [f(a+h) - f(a)] / h as h → 0 exists.

  • Polynomials are differentiable everywhere (for all real numbers).

Example: Modulus function

  • f(x) = x if x ≥ 0; f(x) = -x if x < 0

  • Gradient of secant between (0,0) and (h, f(h)) is:

    • 1 if h > 0

    • -1 if h < 0

  • Left and right limits do not match → derivative does not exist at 0

  • So, f is not differentiable at x = 0.

Derivative function for modulus

  • f'(x) = 1 if x > 0

  • f'(x) = -1 if x < 0


Piecewise differentiability and smooth joins

  • Some piecewise functions are differentiable everywhere if their joins are smooth.

Example 1

  • f(x) = x² + 2x + 1 if x ≥ 0; f(x) = 2x + 1 if x < 0

  • Derivative: f'(x) = 2x + 2 if x ≥ 0; f'(x) = 2 if x < 0

  • f'(0) exists and equals 2 → smooth join → differentiable at 0

Example 2

  • f(x) = x² + 2x + 1 if x ≥ 0; f(x) = x + 1 if x < 0

  • Derivative: f'(x) = 2x + 2 if x > 0; f'(x) = 1 if x < 0

  • f'(0) does not exist (left and right limits differ)

  • Differentiable everywhere except at 0

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Antidifferentiation of Polynomials

  • Antidifferentiation: Finding a function from its derivative.

  • Functions with the same derivative differ by a constant (vertical shifts).

Rules:

  • If F'(x) = f(x), then ∫f(x) dx = F(x) + c (differentiation lose components; any constant).

  • Reverse power rule: ∫xⁿ dx = xⁿ⁺¹ / (n + 1) + c, for n ≠ -1.

  • Linearity:

    • ∫[f(x) + g(x)] dx = ∫f(x) dx + ∫g(x) dx

    • ∫[f(x) − g(x)] dx = ∫f(x) dx − ∫g(x) dx

    • ∫k f(x) dx = k ∫f(x) dx (k constant)

Finding specific antiderivatives (with initial conditions):

  • Use general ∫f'(x) dx + c

  • Plug known point to solve for c

  • Example: f'(x) = 5x, f(0) = 6 → f(x) = 5x²/2 + 6

Examples:

  • ∫3x⁵ dx = 3 × (x⁶ / 6) + c = (1/2) x⁶ + c

  • ∫(3x² + 4x³ + 3) dx = x³ + x⁴ + 3x + c

  • Find f(x) if f'(x) = x³ + 4x² and f(0) = 0:

    • ∫(x³ + 4x²) dx = x⁴/4 + 4x³/3 + c

    • Use initial condition f(0) = 0 → c = 0

    • So f(x) = x⁴/4 + 4x³/3

<ul><li><p class=""><strong>Antidifferentiation: </strong>Finding a function from its derivative.</p></li><li><p class="">Functions with the same derivative differ by a constant (vertical shifts).</p></li></ul><p class=""><strong>Rules:</strong></p><ul><li><p class="">If F'(x) = f(x), then ∫f(x) dx = F(x) <strong><u>+ c (differentiation lose components; any constant)</u></strong>.</p></li><li><p class="">Reverse power rule:<strong> ∫xⁿ dx = xⁿ⁺¹ / (n + 1) + c, for n ≠ -1.</strong></p></li><li><p class="">Linearity:</p><ul><li><p class="">∫[f(x) + g(x)] dx = ∫f(x) dx + ∫g(x) dx</p></li><li><p class="">∫[f(x) − g(x)] dx = ∫f(x) dx − ∫g(x) dx</p></li><li><p class="">∫k f(x) dx = k ∫f(x) dx (k constant)</p></li></ul></li></ul><p class=""><strong>Finding specific antiderivatives (with initial conditions):</strong></p><ul><li><p class="">Use general ∫f'(x) dx + c</p></li><li><p class="">Plug known point to solve for c</p></li><li><p class="">Example: f'(x) = 5x, f(0) = 6 → f(x) = 5x²/2 + 6</p></li></ul><p class=""><strong>Examples:</strong></p><ul><li><p class="">∫3x⁵ dx = 3 × (x⁶ / 6) + c = (1/2) x⁶ + c</p></li><li><p class="">∫(3x² + 4x³ + 3) dx = x³ + x⁴ + 3x + c</p></li><li><p class="">Find f(x) if f'(x) = x³ + 4x² and f(0) = 0:</p><ul><li><p class="">∫(x³ + 4x²) dx = x⁴/4 + 4x³/3 + c</p></li><li><p class="">Use initial condition f(0) = 0 → c = 0</p></li><li><p class="">So f(x) = x⁴/4 + 4x³/3</p></li></ul></li></ul><p></p>
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Antidifferentiating rational powers

  • ∫ x^r dx = x^(r+1) / (r + 1) + c

  • r must be a rational number, not -1

  • Domain of x depends on the value of r

  • ∫ (2x-4 + 6x) dx = -2/3 x-3 + 3x2 + c

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Finding the Exact Area: The Definite Integral

  • It gives the exact area under a curve:
    ∫ₐᵇ f(x) dx = [F(x)] a b = F(b) − F(a)

  • F is any antiderivative of f (thanks to the Fundamental Theorem of Calculus)

  • It’s the limit of Riemann sums as n → ∞

  • Works when f is continuous on [a, b]

  • This is called the definite integral of f(x) with respect to x from x = a to x = b.

  • This is called the fundamental theorem of calculus (cool!).

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Extended, complex version of definite integral

  • The definite integral ∫ₐᵇ f(x) dx is the limit of a sum:
    ∫ₐᵇ f(x) dx = limₙ→∞ Σᵢ₌₁ⁿ f(xᵢ*)Δx

  • Δx = (b − a)/n

  • xᵢ* is a sample point in the i-th subinterval

  • This sum approximates area under f(x); the limit gives the exact value

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Signed area vs Total area

Signed area = ∫ₐᵇ f(x) dx → positive above x-axis, negative below
Total area = ∫ₐᵇ |f(x)| dx → all areas positive

• If f(x) ≥ 0 on [a, b]: Area = ∫ₐᵇ f(x) dx
• If f(x) ≤ 0 on [a, b]: Area = −∫ₐᵇ f(x) dx

• If f(x) changes sign at x = c (a < c < b):
 → Area = −∫ₐᶜ f(x) dx + ∫꜀ᵇ f(x) dx
 → Or Total area = ∫ₐᵇ |f(x)| dx

Geometry tricks:
 – Triangle: ½ × base × height
 – Trapezium: ½ × (a + b) × height

Properties:

• ∫ₐᵇ f(x) dx = −∫ᵦₐ f(x) dx
• ∫ₐᵃ f(x) dx = 0
• ∫ₐᵇ [k·f(x)] dx = k·∫ₐᵇ f(x) dx
• ∫ₐᵇ [f(x) ± g(x)] dx = ∫ₐᵇ f(x) dx ± ∫ₐᵇ g(x) dx
∫ₐᵇ f(x) dx = ∫ₐᶜ f(x) dx + ∫꜀ᵇ f(x) dx

Tips:

🧠 Use the split rule when the function changes sign or form mid-way.

<p>• <strong>Signed area</strong> = ∫ₐᵇ f(x) dx → <strong>positive</strong> above x-axis, <strong>negative</strong> below<br>• <strong>Total area</strong> = ∫ₐᵇ |f(x)| dx → all areas <strong>positive</strong></p><p class="">• If <strong>f(x) ≥ 0</strong> on [a, b]: <strong>Area</strong> = ∫ₐᵇ f(x) dx<br>• If <strong>f(x) ≤ 0</strong> on [a, b]: <strong>Area</strong> = −∫ₐᵇ f(x) dx</p><p class="">• If <strong>f(x)</strong> changes sign at <strong>x = c</strong> (a &lt; c &lt; b):<br> → <strong>Area</strong> = −∫ₐᶜ f(x) dx + ∫꜀ᵇ f(x) dx<br> → Or <strong>Total area</strong> = ∫ₐᵇ |f(x)| dx</p><p class="">• <strong>Geometry tricks</strong>:<br> – Triangle: ½ × base × height<br> – Trapezium: ½ × (a + b) × height</p><p class=""><strong>Properties:</strong></p><p class="">• ∫ₐᵇ f(x) dx = −∫ᵦₐ f(x) dx<br>• ∫ₐᵃ f(x) dx = 0<br>• ∫ₐᵇ [k·f(x)] dx = k·∫ₐᵇ f(x) dx<br>• ∫ₐᵇ [f(x) ± g(x)] dx = ∫ₐᵇ f(x) dx ± ∫ₐᵇ g(x) dx<br>• <strong>∫ₐᵇ f(x) dx = ∫ₐᶜ f(x) dx + ∫꜀ᵇ f(x) dx</strong></p><p class=""><strong>Tips:</strong></p><p class=""><span data-name="brain" data-type="emoji">🧠</span> Use the <em>split rule</em> when the function changes sign or form mid-way.</p>
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Estimating Area

Divide the interval [a, b] on the x-axis into n equal subintervals [x₀, x₁], [x₁, x₂], [x₂, x₃], …, [xₙ₋₁, xₙ] as illustrated.
Estimates for the area under the graph of y = f(x) between x = a and x = b:

Left-endpoint estimate
Lₙ = (b − a)/n × [f(x₀) + f(x₁) + ··· + f(xₙ₋₁)]

Right-endpoint estimate
Rₙ = (b − a)/n × [f(x₁) + f(x₂) + ··· + f(xₙ)]

Trapezoidal estimate
Tₙ = (b − a)/(2n) × [f(x₀) + 2f(x₁) + 2f(x₂) + ··· + 2f(xₙ₋₁) + f(xₙ)]
These methods work for any continuous function on [a, b], regardless of whether the graph is increasing or decreasing.