AP CALCULUS BC NEED-TO-KNOWS !

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Last updated 6:07 AM on 5/8/26
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104 Terms

1
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Euler's Method

yn+1=yn+hf(xn,yn)y_{n+1} = y_n + h \cdot f(x_n, y_n), where hh is the step size

2
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Logistic Growth Rate

dPdt=kP(1PM)\frac{dP}{dt} = kP\left(1 - \frac{P}{M}\right), where MM is carrying capacity

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Logistic max growth rate

occurs at P=M2P = \frac{M}{2}; rate =kM24= \frac{kM^2}{4}

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Logistic curve shape

S-shaped; concave up when P<M2P < \frac{M}{2}, concave down when P>M2P > \frac{M}{2}, inflection at P=M2P = \frac{M}{2}

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Separable Differential Equation

rewrite as g(y)dy=f(x)dxg(y)\,dy = f(x)\,dx, then integrate both sides independently

6
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Taylor Series (centered at cc)

f(x)=n=0f(n)(c)n!(xc)nf(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(c)}{n!}(x-c)^n

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Maclaurin Series

f(x)=n=0f(n)(0)n!xnf(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n!}x^n

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Maclaurin Series for exe^x

ex=n=0xnn!=1+x+x22!+x33!+e^x = \sum_{n=0}^{\infty} \frac{x^n}{n!} = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots

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Maclaurin Series for sinx\sin x

sinx=n=0(1)nx2n+1(2n+1)!=xx33!+x55!\sin x = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{(2n+1)!} = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \cdots

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Maclaurin Series for cosx\cos x

cosx=n=0(1)nx2n(2n)!=1x22!+x44!\cos x = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n}}{(2n)!} = 1 - \frac{x^2}{2!} + \frac{x^4}{4!} - \cdots

11
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Maclaurin Series for 11x\frac{1}{1-x}

11x=n=0xn=1+x+x2+\frac{1}{1-x} = \sum_{n=0}^{\infty} x^n = 1 + x + x^2 + \cdots, |x| < 1

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Sum of infinite geometric series

S=a1rS = \frac{a}{1-r}, valid when |r| < 1

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nth Term Test (Divergence Test)

If limnan0\lim_{n\to\infty} a_n \neq 0, the series diverges. If =0= 0, inconclusive.

14
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Geometric Series Test

arn\sum ar^n converges to a1r\frac{a}{1-r} when |r|<1; diverges when r1|r|\geq 1

15
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p-Series Test

1np\sum \frac{1}{n^p} converges if p > 1; diverges if p1p \leq 1

16
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Integral Test

If ff is positive, continuous, and decreasing, then an\sum a_n and f(x)dx\int f(x)\,dx both converge or both diverge

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Direct Comparison Test

If 0anbn0 \leq a_n \leq b_n: bn\sum b_n converges \Rightarrow an\sum a_n converges; an\sum a_n diverges \Rightarrow bn\sum b_n diverges

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Limit Comparison Test

If \lim \frac{a_n}{b_n} = L > 0 (finite), then an\sum a_n and bn\sum b_n both converge or both diverge

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Alternating Series Test

(1)nbn\sum(-1)^n b_n converges if (1) bnb_n is decreasing and (2) limnbn=0\lim_{n\to\infty} b_n = 0

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Alternating Series Estimation Theorem

Errorbn+1|\text{Error}| \leq b_{n+1}

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Ratio Test

liman+1an<1\lim\left|\frac{a_{n+1}}{a_n}\right| < 1 \Rightarrow converges; >1> 1 \Rightarrow diverges; =1= 1 \Rightarrow inconclusive

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Radius of Convergence

R=1liman+1/anR = \frac{1}{\lim|a_{n+1}/a_n|}; series converges for |x-c| < R

23
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Absolute vs. Conditional Convergence

Absolutely convergent: an\sum|a_n| converges. Conditionally convergent: an\sum a_n converges but an\sum|a_n| diverges.

24
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Lagrange Error Bound

f(x)Pn(x)Mxcn+1(n+1)!|f(x)-P_n(x)| \leq \frac{M|x-c|^{n+1}}{(n+1)!}, where Mf(n+1)(t)M \geq |f^{(n+1)}(t)| for all tt between xx and cc

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First Derivative (parametric)

dydx=dy/dtdx/dt\frac{dy}{dx} = \frac{dy/dt}{dx/dt}

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Second Derivative (parametric)

d2ydx2=ddt(dy/dx)dx/dt\frac{d^2y}{dx^2} = \frac{\frac{d}{dt}(dy/dx)}{dx/dt}

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Arc Length (parametric)

L=ab(dxdt)2+(dydt)2dtL = \int_a^b \sqrt{\left(\frac{dx}{dt}\right)^2 + \left(\frac{dy}{dt}\right)^2}\,dt

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Position vector

x(t),y(t)\langle x(t), y(t) \rangle

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Velocity vector

x(t),y(t)\langle x'(t), y'(t) \rangle

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Acceleration vector

x(t),y(t)\langle x''(t), y''(t) \rangle

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Speed (parametric)

(x(t))2+(y(t))2\sqrt{(x'(t))^2 + (y'(t))^2}

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Polar Conversions

x=rcosθx = r\cos\theta, y=rsinθy = r\sin\theta, r2=x2+y2r^2 = x^2+y^2, tanθ=yx\tan\theta = \frac{y}{x}

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Polar Area

A=12αβr2dθA = \frac{1}{2}\int_\alpha^\beta r^2\,d\theta

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Polar Slope

dydx=drdθsinθ+rcosθdrdθcosθrsinθ\frac{dy}{dx} = \frac{\frac{dr}{d\theta}\sin\theta + r\cos\theta}{\frac{dr}{d\theta}\cos\theta - r\sin\theta}

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Position

x(t)=v(t)dtx(t) = \int v(t)\,dt

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Velocity

v(t)=x(t)=a(t)dtv(t) = x'(t) = \int a(t)\,dt

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Acceleration

a(t)=v(t)=x(t)a(t) = v'(t) = x''(t)

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Speed

v(t)|v(t)|, always non-negative

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Displacement

abv(t)dt\int_a^b v(t)\,dt, net change in position (can be negative)

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Total Distance

abv(t)dt\int_a^b |v(t)|\,dt, always non-negative

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New Position

s(a)+abv(t)dts(a) + \int_a^b v(t)\,dt

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Average Velocity

x(t2)x(t1)t2t1\frac{x(t_2)-x(t_1)}{t_2-t_1}

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Speed increasing

when a(t)a(t) and v(t)v(t) have the same sign

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Speed decreasing

when a(t)a(t) and v(t)v(t) have opposite signs

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Particle at rest

v(t)=0v(t) = 0

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Particle moves right/up

v(t) > 0

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Particle moves left/down

v(t) < 0

48
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Integration by Parts

udv=uvvdu\int u\,dv = uv - \int v\,du

49
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Average Value of a Function

favg=1baabf(x)dxf_{\text{avg}} = \frac{1}{b-a}\int_a^b f(x)\,dx

50
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Reverse Power Rule (Integration)

xndx=xn+1n+1+C\int x^n\,dx = \frac{x^{n+1}}{n+1} + C, n1n \neq -1

51
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cosudu\int \cos u\,du

sinu+C\sin u + C

52
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sinudu\int \sin u\,du

cosu+C-\cos u + C

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eudu\int e^u\,du

eu+Ce^u + C

54
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u1du\int u^{-1}\,du

lnu+C\ln|u| + C

55
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Disk Method

V=πab[f(x)]2dxV = \pi\int_a^b [f(x)]^2\,dx

56
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Washer Method

V=πab([R(x)]2[r(x)]2)dxV = \pi\int_a^b \left([R(x)]^2 - [r(x)]^2\right)dx, where RR = outer radius, rr = inner radius

57
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General Volume (cross-sections)

V=abA(x)dxV = \int_a^b A(x)\,dx, where A(x)A(x) is the cross-sectional area

58
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Area Between Two Curves

A=ab[f(x)g(x)]dxA = \int_a^b [f(x) - g(x)]\,dx, where f(x)g(x)f(x) \geq g(x)

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Arc Length (rectangular)

L=ab1+[f(x)]2dxL = \int_a^b \sqrt{1 + [f'(x)]^2}\,dx

60
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Mean Value Theorem (MVT)

If ff is continuous on [a,b][a,b] and differentiable on (a,b)(a,b), then c(a,b)\exists\, c \in (a,b) where f(c)=f(b)f(a)baf'(c) = \frac{f(b)-f(a)}{b-a}

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Fundamental Theorem of Calculus (FTC 1)

abf(x)dx=F(b)F(a)\int_a^b f(x)\,dx = F(b) - F(a), where F=fF' = f

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Fundamental Theorem of Calculus (FTC 2)

ddx0g(x)f(t)dt=f(g(x))g(x)\frac{d}{dx}\int_0^{g(x)} f(t)\,dt = f(g(x)) \cdot g'(x)

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Rolle's Theorem

If ff is continuous on [a,b][a,b], differentiable on (a,b)(a,b), and f(a)=f(b)f(a)=f(b), then c\exists\, c where f(c)=0f'(c)=0

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Critical Points

Where f=0f'=0 or ff' is undefined

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Relative Minimum

Where ff' changes from negative to positive; f''>0 confirms concave up

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Relative Maximum

Where ff' changes from positive to negative; f''<0 confirms concave down

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Point of Inflection

Where ff'' changes sign; verify sign change, not just f=0f''=0

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Absolute Extrema

Occur at critical points or endpoints; evaluate ff at all and compare

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Definition of Derivative

f(x)=limh0f(x+h)f(x)hf'(x) = \lim_{h \to 0} \frac{f(x+h)-f(x)}{h}

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Alternate Definition of Derivative

f(x)<em>x=a=lim</em>xaf(x)f(a)xaf'(x)\big|<em>{x=a} = \lim</em>{x \to a} \frac{f(x)-f(a)}{x-a}

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Chain Rule

ddx[f(u)]=f(u)u\frac{d}{dx}[f(u)] = f'(u) \cdot u'

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Product Rule

ddx[fg]=fg+gf\frac{d}{dx}[fg] = f'g + gf'

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Quotient Rule

ddx[fg]=gffgg2\frac{d}{dx}\left[\frac{f}{g}\right] = \frac{gf' - fg'}{g^2}

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Power Rule

ddx(xn)=nxn1\frac{d}{dx}(x^n) = nx^{n-1}

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ddx(sinu)\frac{d}{dx}(\sin u)

cosuu\cos u \cdot u'

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ddx(cosu)\frac{d}{dx}(\cos u)

sinuu-\sin u \cdot u'

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ddx(tanu)\frac{d}{dx}(\tan u)

sec2uu\sec^2 u \cdot u'

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ddx(cotu)\frac{d}{dx}(\cot u)

csc2uu-\csc^2 u \cdot u'

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ddx(secu)\frac{d}{dx}(\sec u)

secutanuu\sec u \tan u \cdot u'

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ddx(cscu)\frac{d}{dx}(\csc u)

cscucotuu-\csc u \cot u \cdot u'

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ddx(lnu)\frac{d}{dx}(\ln u)

uu\frac{u'}{u}

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ddx(eu)\frac{d}{dx}(e^u)

euue^u \cdot u'

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ddx(u)\frac{d}{dx}(\sqrt{u})

u2u\frac{u'}{2\sqrt{u}}

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ddx(sin1u)\frac{d}{dx}(\sin^{-1} u)

u1u2\frac{u'}{\sqrt{1-u^2}}

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ddx(cos1u)\frac{d}{dx}(\cos^{-1} u)

u1u2\frac{-u'}{\sqrt{1-u^2}}

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ddx(tan1u)\frac{d}{dx}(\tan^{-1} u)

u1+u2\frac{u'}{1+u^2}

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ddx(cot1u)\frac{d}{dx}(\cot^{-1} u)

u1+u2\frac{-u'}{1+u^2}

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Limit from the left

limxcf(x)\lim_{x \to c^-} f(x): the value f(x)f(x) approaches as xx approaches cc from below.

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Limit from the right

limxc+f(x)\lim_{x \to c^+} f(x): the value f(x)f(x) approaches as xx approaches cc from above.

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Two-sided limit exists when

limxcf(x)=limxc+f(x)\lim_{x \to c^-} f(x) = \lim_{x \to c^+} f(x)

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Limits fail to exist when

(1) left \neq right limit, (2) vertical asymptote, (3) oscillation (e.g., sin(1/x)\sin(1/x) near 0)

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Definition of Continuity at x=cx = c

ff is continuous iff: (1) f(c)f(c) exists, (2) limxcf(x)\lim_{x \to c} f(x) exists, (3) limxcf(x)=f(c)\lim_{x \to c} f(x) = f(c)

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Derivatives fail to exist when

(1) not continuous, (2) sharp corner/cusp, (3) vertical tangent line

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Intermediate Value Theorem (IVT)

If ff is continuous on [a,b][a,b] and kk is between f(a)f(a) and f(b)f(b), then c(a,b)\exists\, c \in (a,b) such that f(c)=kf(c) = k

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Extreme Value Theorem (EVT)

If ff is continuous on closed [a,b][a,b], then ff has both an absolute maximum and minimum on that interval

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L'Hopital's Rule

If limf(x)g(x)\lim \frac{f(x)}{g(x)} gives 00\frac{0}{0} or \frac{\infty}{\infty}, then limf(x)g(x)=limf(x)g(x)\lim \frac{f(x)}{g(x)} = \lim \frac{f'(x)}{g'(x)}

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limx0sinxx\lim_{x \to 0} \frac{\sin x}{x}

11

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limx01cosxx\lim_{x \to 0} \frac{1 - \cos x}{x}

00

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limx0tanxx\lim_{x \to 0} \frac{\tan x}{x}

11

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limx(1+1x)x\lim_{x \to \infty} \left(1 + \frac{1}{x}\right)^x

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