Calculus BC

AP Calculus BC — Cheatsheet

Formulas, exam-day tips, and key terms on one page.

Formulas & relationships

Existence of a two-sided limit
lim(x→a) f(x) = L ⟺ lim(x→a⁻) f(x) = L and lim(x→a⁺) f(x) = L
Both one-sided limits must exist and be equal. If they differ, the two-sided limit does not exist.
Two limits worth memorizing
lim(x→0) sin(x)/x = 1 · lim(x→0) (1 − cos x)/x = 0
These special trig limits appear constantly; direct substitution gives 0/0, but the true limits are 1 and 0.
Continuity at a point
f continuous at a ⟺ f(a) defined and lim(x→a) f(x) exists and lim(x→a) f(x) = f(a)
All three parts are required. The equality in the third part is the one students most often skip.
End behavior of rational functions
deg(bottom) > deg(top): limit 0 · equal degrees: ratio of leading coefficients · deg(top) > deg(bottom): ±∞
These three cases decide the horizontal asymptote (or its absence) as x → ±∞.
Intermediate Value Theorem
f continuous on [a, b] and N between f(a) and f(b) ⟹ ∃ c in (a, b) with f(c) = N
An existence theorem: it promises a c exists but gives no formula for it.
Limit definition of the derivative
f′(x) = lim(h→0) [f(x + h) − f(x)] / h
The difference quotient [f(x+h) − f(x)]/h is the secant slope; its limit as h→0 is the tangent slope.
Product and quotient rules
(fg)′ = f′g + fg′ · (f/g)′ = (f′g − fg′) / g²
The quotient rule numerator is "low d-high minus high d-low"; the order of subtraction matters.
Differentiability at a seam
f differentiable at c ⟺ f continuous at c AND lim(x→c⁻) f′(x) = lim(x→c⁺) f′(x)
Both conditions, in that order. Matching slopes alone is not enough — a function can have equal one-sided slopes across a jump.
Estimating a derivative from a table
f′(a) ≈ [f(a + h) − f(a − h)] / (2h) · one-sided: [f(b) − f(a)] / (b − a)
Symmetric when values bracket the point; the divisor is always the distance between the two x-values used.
The chain rule
d/dx [ f(g(x)) ] = f′(g(x)) · g′(x)
Derivative of the outer (with the inner left inside) times the derivative of the inner. In Leibniz form: dy/dx = (dy/du)(du/dx).
Differentiating a y-term
d/dx [ y³ ] = 3y² · (dy/dx) · d/dx [ x·y ] = y + x·(dy/dx)
A y raised to a power picks up dy/dx by the chain rule; a product of x and y needs the product rule too.
Derivative of an inverse function
If g = f⁻¹ and f(a) = b, then g′(b) = 1 / f′(a) = 1 / f′(g(b)).
The slope of the inverse at b is the reciprocal of the slope of f at the matching input a.
Inverse trig derivatives
d/dx[arcsin x] = 1/√(1 − x²) · d/dx[arctan x] = 1/(1 + x²) · d/dx[arcsec x] = 1/(|x|√(x² − 1))
arccos, arccot, and arccsc are just the negatives of arcsin, arctan, and arcsec respectively.
Chain rule, three layers
d/dx f(g(h(x))) = f′(g(h(x))) · g′(h(x)) · h′(x)
One factor per layer. The count of factors should equal the count of function layers — a quick check that nothing was dropped.
The motion chain and distance
v(t) = x′(t) · a(t) = v′(t) · total distance = ∫ₐᵇ |v(t)| dt
Displacement is ∫v dt (signed); total distance is the integral of |v| (unsigned), splitting at direction changes.
Differentiating a volume relation in time
V = (4/3)πr³ ⟹ dV/dt = 4πr² · (dr/dt)
Every geometric formula becomes a rate equation once differentiated with respect to t via the chain rule.
Linearization at x = a
L(x) = f(a) + f′(a)(x − a) · f(x) ≈ L(x) for x near a
Concave up on the interval ⇒ L underestimates. Concave down ⇒ L overestimates.
L’Hôpital’s Rule
If lim f/g is 0/0 or ∞/∞, then lim f(x)/g(x) = lim f′(x)/g′(x)
Check the form on every pass, including after each application. Stop as soon as the form is no longer indeterminate.
Mean Value Theorem
f′(c) = [ f(b) − f(a) ] / (b − a) for some c in (a, b)
The right side is the secant slope (average rate); f′(c) is the tangent slope (instantaneous rate). MVT guarantees they match at some c.
First Derivative Test at a critical point c
f′: + → − ⇒ relative max · f′: − → + ⇒ relative min · no sign change ⇒ neither
The conclusion comes from the sign change of f′ across c, not from the value of f at c.
Concavity and the Second Derivative Test
f″ > 0 ⇒ concave up ⇒ relative min at a critical point · f″ < 0 ⇒ concave down ⇒ relative max · f″ = 0 ⇒ inconclusive
Inflection points need a sign change in f″, which f″ = 0 alone does not guarantee.
Translating between f, f′ and f″
f ↑ ⟺ f′ > 0 · f rel. extremum ⟺ f′ changes sign · f concave up ⟺ f′ ↑ ⟺ f″ > 0 · f inflection ⟺ f′ has an extremum
Every question about f from a graph of f′ is one of these four rows.
First-derivative test for a maximum
If f′ changes + → − at c, then f has a local maximum at c.
A sign change from positive to negative means the function rises then falls — a peak. The reverse (− → +) is a local minimum.
Trapezoidal sum, unequal widths
Σ [(f(xᵢ) + f(xᵢ₊₁))/2] · (xᵢ₊₁ − xᵢ) · equal widths: (Δx/2)[f(x₀) + 2f(x₁) + … + 2f(xₙ₋₁) + f(xₙ)]
The h/2 shortcut with doubled interior terms is valid only when every subinterval has the same width.
FTC Part 1 (with the chain rule)
d/dx ∫ₐ^{u(x)} f(t) dt = f(u(x)) · u′(x)
When the upper limit is a function u(x) rather than plain x, multiply by u′(x). This chain-rule twist is heavily tested.
FTC Part 2 (evaluation)
∫ₐᵇ f(x) dx = F(b) − F(a), where F′ = f
Any antiderivative works — the constant of integration cancels in the subtraction.
Second Fundamental Theorem, with the chain rule
d/dx ∫ₐˣ f(t) dt = f(x) · d/dx ∫ₐ^(u(x)) f(t) dt = f(u(x)) · u′(x)
g″(x) = f′(x), so the concavity of the accumulation function is the increase or decrease of the integrand.
Definite integral by substitution
∫ₐᵇ f(g(x))·g′(x) dx = ∫_(g(a))^(g(b)) f(u) du
The new limits are the old ones passed through g. Once the limits are converted, never substitute back.
Integration by parts
∫ u dv = u·v − ∫ v du
You pick u (to differentiate) and dv (to integrate); then du = u′ dx and v = ∫dv.
Decomposition over distinct linear factors
P(x) / [(x − a)(x − b)] = A/(x − a) + B/(x − b)
One unknown constant per distinct linear factor. Solve for A and B by clearing denominators and substituting convenient x-values.
Improper integral over an infinite interval
∫ₐ^∞ f(x) dx = lim(b→∞) ∫ₐᵇ f(x) dx
Convert the infinite bound to a finite b, integrate, then let b → ∞. A finite result means convergence.
What a slope field encodes
At each point (x, y), segment slope = dy/dx = f(x, y)
The field is the geometry of the equation; a solution curve threads through it tangent to every segment.
The exponential model
dy/dt = ky, y(0) = y₀ ⇒ y = y₀e^(kt)
Growth for k > 0, decay for k < 0. Contrast with the logistic dy/dt = ky(L − y), whose growth levels off at the carrying capacity L.
Exponential growth/decay model
dy/dt = k·y ⟹ y = y₀·e^{kt}
The classic separable equation: rate proportional to amount. k > 0 is growth, k < 0 is decay; y₀ is the initial amount.
Euler’s method update
x_{n+1} = x_n + Δx · y_{n+1} = y_n + f(x_n, y_n)·Δx
The new y is the old y plus slope times step size. "Rise = slope × run" applied one step at a time.
Logistic differential equation
dP/dt = kP(1 − P/M)
M is the carrying capacity. Growth rate is near-exponential for small P and falls to 0 as P → M.
Average value of a function
f_avg = (1/(b − a)) · ∫ₐᵇ f(x) dx
Integrate, then divide by the length of the interval. Do not confuse with average rate of change, [f(b) − f(a)]/(b − a).
Motion and net change
displacement = ∫ₐᵇ v(t) dt · total distance = ∫ₐᵇ |v(t)| dt · F(b) = F(a) + ∫ₐᵇ F′(t) dt
Position at a later time needs an initial position; the integral supplies only the change.
Area between curves
A = ∫ₐᵇ [ f(x) − g(x) ] dx, with f on top and g on the bottom
Integrate top minus bottom. If integrating in y instead, it becomes right minus left: ∫ [x_right − x_left] dy.
Disk and washer methods
disk: V = π ∫ₐᵇ [R(x)]² dx · washer: V = π ∫ₐᵇ ([R(x)]² − [r(x)]²) dx
R is the outer radius (to the far edge), r the inner radius (to the hole). Use a washer whenever the region does not touch the axis.
Arc length of y = f(x)
L = ∫ₐᵇ √( 1 + (dy/dx)² ) dx
Comes from the Pythagorean length √(dx² + dy²) of each infinitesimal piece, factored to pull out dx.
Parametric first derivative
dy/dx = (dy/dt) / (dx/dt), provided dx/dt ≠ 0
The slope of the curve is the ratio of the two t-derivatives — a direct consequence of the chain rule.
Parametric derivatives
dy/dx = (dy/dt)/(dx/dt) · d²y/dx² = [d/dt (dy/dx)] / (dx/dt)
Differentiate the slope expression with respect to t, then divide by dx/dt once more. Never divide the second t-derivatives.
Parametric arc length
L = ∫ₐᵇ √( (dx/dt)² + (dy/dt)² ) dt
Identical to the integral of speed over time, so arc length = total distance traveled by the particle.
Speed as the magnitude of velocity
speed = |v(t)| = √( (dx/dt)² + (dy/dt)² )
Speed is a scalar: the length of the velocity vector. Velocity carries direction; speed is just how fast.
Area enclosed by a polar curve
A = ½ ∫_α^β [ r(θ) ]² dθ
The ½r² comes from the area of a circular sector. Integrate over the θ-interval that traces the region exactly once.
Polar area and slope
A = (1/2)∫ᵅᵝ r² dθ · between curves: (1/2)∫ᵅᵝ (r_outer² − r_inner²) dθ · dy/dx = (dy/dθ)/(dx/dθ)
Square first, then subtract. (r₁ − r₂)² is not r₁² − r₂².
Geometric series and the nth-term test
Σ arⁿ = a/(1 − r) for |r| < 1, divergent otherwise · lim aₙ ≠ 0 ⇒ Σaₙ diverges
aₙ → 0 does NOT imply convergence. The nth-term test proves divergence only.
Two benchmark series
geometric Σ arⁿ: converges ⟺ |r| < 1, to a/(1 − r) · p-series Σ 1/nᵖ: converges ⟺ p > 1
These two are the reference points most comparison and ratio arguments lean on.
The tests, with their conditions
p-series: Σ1/n^p converges ⟺ p > 1 · Ratio: lim|aₙ₊₁/aₙ| = L, converges if L < 1, diverges if L > 1, inconclusive if L = 1 · Alternating: terms decreasing in magnitude AND → 0
The ratio test at L = 1 says nothing at all — that is exactly where p-series live, and where a comparison is needed instead.
Taylor series centered at a
f(x) = Σ (n=0 to ∞) [ fⁿ(a) / n! ] (x − a)ⁿ = f(a) + f′(a)(x−a) + [f″(a)/2!](x−a)² + …
The nth coefficient is fⁿ(a)/n!. Setting a = 0 gives the Maclaurin series.
Alternating series error bound
| S − Sₙ | ≤ | a_{n+1} |
For a convergent alternating series, the error after n terms is no larger than the absolute value of the first omitted term.
Lagrange error bound
| Rₙ(x) | ≤ ( M / (n+1)! ) · | x − a |ⁿ⁺¹
M is a bound on |f^(n+1)| on the interval between a and x. Controls the error of the nth-degree Taylor polynomial.
Radius of convergence via the ratio test
lim |cₙ₊₁(x − a)ⁿ⁺¹ / cₙ(x − a)ⁿ| < 1 ⟹ |x − a| < R
Apply the ratio test, solve the resulting inequality for |x − a|; the bound is R. Then test x = a ± R by hand.
The four required Maclaurin series
e^x = Σ xⁿ/n! (all x) · sin x = Σ (−1)ⁿx^(2n+1)/(2n+1)! (all x) · cos x = Σ (−1)ⁿx^(2n)/(2n)! (all x) · 1/(1−x) = Σ xⁿ (|x| < 1)
sin has odd powers and cos has even ones — checking the parity of the exponents catches a swapped pair instantly.

On the exam

How to get a 5

Key terms

Derivative of tan xsec²x
Derivative of arctan x1/(1 + x²)
∫ 1/(a² + x²) dx(1/a) arctan(x/a) + C
Integration by parts∫u dv = uv − ∫v du. Choose u by LIATE — logarithmic, inverse trig, algebraic, trigonometric, exponential — taking the earliest type as u.
Maclaurin series for eˣΣ xⁿ/n! = 1 + x + x²/2! + x³/3! + …
Maclaurin series for sin xΣ (−1)ⁿ x²ⁿ⁺¹/(2n+1)! = x − x³/3! + x⁵/5! − …
Arc length of y = f(x) on [a,b]∫ₐᵇ √(1 + (f'(x))²) dx
Area inside polar curve r = f(θ)(1/2) ∫_α^β [f(θ)]² dθ
Parametric dy/dx(dy/dt)/(dx/dt), provided dx/dt ≠ 0
p-series convergenceΣ 1/nᵖ converges if p > 1; diverges if p ≤ 1.
Logistic equation & carrying capacitydP/dt = kP(1 − P/L); grows fastest at P = L/2, limit L.
Lagrange error bound|Rₙ(x)| ≤ M|x − a|ⁿ⁺¹/(n + 1)!, where M bounds the (n+1)th derivative on the interval. State what M is and why.
L’Hôpital’s rule (when it applies)Only for 0/0 or ∞/∞ forms: replace f/g by f′/g′ and re-take the limit. Always confirm the indeterminate form first.
Partial fraction decompositionFor proper rational functions with factorable denominators: split into A/(x − a) + B/(x − b), solve for constants, integrate to logarithms.
Improper integralAn integral with an infinite limit or an unbounded integrand; evaluate as a limit. ∫₁^∞ 1/xᵖ converges iff p > 1; ∫₀¹ 1/xᵖ converges iff p < 1.
Arc length (function form)L = ∫ₐᵇ √(1 + (f′(x))²) dx.
Euler’s methodRepeated tangent-line steps: yₙ₊₁ = yₙ + Δx·f(xₙ, yₙ), always using the slope at the current point.
Logistic differential equationdP/dt = kP(1 − P/L). Growth is nearly exponential when P is small and slows to zero as P approaches the carrying capacity L.
Parametric derivativedy/dx = (dy/dt)/(dx/dt), defined wherever dx/dt ≠ 0. Not the derivative of y with respect to t.
Parametric arc length / distance traveledL = ∫√((dx/dt)² + (dy/dt)²) dt — the integral of speed.
Speed of a vector-valued particle|v(t)| = √((x′)² + (y′)²); speed is a scalar, direction lives in the velocity vector.
Polar area formulaA = (1/2)∫ r² dθ over the sweep of the region — do not forget the 1/2.
Polar to rectangular slopedy/dx = (dy/dθ)/(dx/dθ) with x = r cos θ, y = r sin θ (product rule in θ since r depends on θ).
Geometric seriesΣarⁿ converges to a/(1 − r) when |r| < 1 and diverges otherwise. The only common series whose exact sum is easy to state.