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Euler's Method
yn+1=yn+h⋅f(xn,yn), where h is the step size
Logistic Growth Rate
dtdP=kP(1−MP), where M is carrying capacity
Logistic max growth rate
occurs at P=2M; rate =4kM2
Logistic curve shape
S-shaped; concave up when P<2M, concave down when P>2M, inflection at P=2M
Separable Differential Equation
rewrite as g(y)dy=f(x)dx, then integrate both sides independently
Taylor Series (centered at c)
f(x)=n=0∑∞n!f(n)(c)(x−c)n
Maclaurin Series
f(x)=n=0∑∞n!f(n)(0)xn
Maclaurin Series for ex
ex=n=0∑∞n!xn=1+x+2!x2+3!x3+⋯
Maclaurin Series for sinx
sinx=n=0∑∞(2n+1)!(−1)nx2n+1=x−3!x3+5!x5−⋯
Maclaurin Series for cosx
cosx=n=0∑∞(2n)!(−1)nx2n=1−2!x2+4!x4−⋯
Maclaurin Series for 1−x1
1−x1=∑n=0∞xn=1+x+x2+⋯, |x| < 1
Sum of infinite geometric series
S=1−ra, valid when |r| < 1
nth Term Test (Divergence Test)
If limn→∞an=0, the series diverges. If =0, inconclusive.
Geometric Series Test
∑arn converges to 1−ra when |r|<1; diverges when ∣r∣≥1
p-Series Test
∑np1 converges if p > 1; diverges if p≤1
Integral Test
If f is positive, continuous, and decreasing, then ∑an and ∫f(x)dx both converge or both diverge
Direct Comparison Test
If 0≤an≤bn: ∑bn converges ⇒ ∑an converges; ∑an diverges ⇒ ∑bn diverges
Limit Comparison Test
If \lim \frac{a_n}{b_n} = L > 0 (finite), then ∑an and ∑bn both converge or both diverge
Alternating Series Test
∑(−1)nbn converges if (1) bn is decreasing and (2) limn→∞bn=0
Alternating Series Estimation Theorem
∣Error∣≤bn+1
Ratio Test
limanan+1<1⇒ converges; >1⇒ diverges; =1⇒ inconclusive
Radius of Convergence
R=lim∣an+1/an∣1; series converges for |x-c| < R
Absolute vs. Conditional Convergence
Absolutely convergent: ∑∣an∣ converges. Conditionally convergent: ∑an converges but ∑∣an∣ diverges.
Lagrange Error Bound
∣f(x)−Pn(x)∣≤(n+1)!M∣x−c∣n+1, where M≥∣f(n+1)(t)∣ for all t between x and c
First Derivative (parametric)
dxdy=dx/dtdy/dt
Second Derivative (parametric)
dx2d2y=dx/dtdtd(dy/dx)
Arc Length (parametric)
L=∫ab(dtdx)2+(dtdy)2dt
Position vector
⟨x(t),y(t)⟩
Velocity vector
⟨x′(t),y′(t)⟩
Acceleration vector
⟨x′′(t),y′′(t)⟩
Speed (parametric)
(x′(t))2+(y′(t))2
Polar Conversions
x=rcosθ, y=rsinθ, r2=x2+y2, tanθ=xy
Polar Area
A=21∫αβr2dθ
Polar Slope
dxdy=dθdrcosθ−rsinθdθdrsinθ+rcosθ
Position
x(t)=∫v(t)dt
Velocity
v(t)=x′(t)=∫a(t)dt
Acceleration
a(t)=v′(t)=x′′(t)
Speed
∣v(t)∣, always non-negative
Displacement
∫abv(t)dt, net change in position (can be negative)
Total Distance
∫ab∣v(t)∣dt, always non-negative
New Position
s(a)+∫abv(t)dt
Average Velocity
t2−t1x(t2)−x(t1)
Speed increasing
when a(t) and v(t) have the same sign
Speed decreasing
when a(t) and v(t) have opposite signs
Particle at rest
v(t)=0
Particle moves right/up
v(t) > 0
Particle moves left/down
v(t) < 0
Integration by Parts
∫udv=uv−∫vdu
Average Value of a Function
favg=b−a1∫abf(x)dx
Reverse Power Rule (Integration)
∫xndx=n+1xn+1+C, n=−1
∫cosudu
sinu+C
∫sinudu
−cosu+C
∫eudu
eu+C
∫u−1du
ln∣u∣+C
Disk Method
V=π∫ab[f(x)]2dx
Washer Method
V=π∫ab([R(x)]2−[r(x)]2)dx, where R = outer radius, r = inner radius
General Volume (cross-sections)
V=∫abA(x)dx, where A(x) is the cross-sectional area
Area Between Two Curves
A=∫ab[f(x)−g(x)]dx, where f(x)≥g(x)
Arc Length (rectangular)
L=∫ab1+[f′(x)]2dx
Mean Value Theorem (MVT)
If f is continuous on [a,b] and differentiable on (a,b), then ∃c∈(a,b) where f′(c)=b−af(b)−f(a)
Fundamental Theorem of Calculus (FTC 1)
∫abf(x)dx=F(b)−F(a), where F′=f
Fundamental Theorem of Calculus (FTC 2)
dxd∫0g(x)f(t)dt=f(g(x))⋅g′(x)
Rolle's Theorem
If f is continuous on [a,b], differentiable on (a,b), and f(a)=f(b), then ∃c where f′(c)=0
Critical Points
Where f′=0 or f′ is undefined
Relative Minimum
Where f′ changes from negative to positive; f''>0 confirms concave up
Relative Maximum
Where f′ changes from positive to negative; f''<0 confirms concave down
Point of Inflection
Where f′′ changes sign; verify sign change, not just f′′=0
Absolute Extrema
Occur at critical points or endpoints; evaluate f at all and compare
Definition of Derivative
f′(x)=h→0limhf(x+h)−f(x)
Alternate Definition of Derivative
f′(x)<em>x=a=lim</em>x→ax−af(x)−f(a)
Chain Rule
dxd[f(u)]=f′(u)⋅u′
Product Rule
dxd[fg]=f′g+gf′
Quotient Rule
dxd[gf]=g2gf′−fg′
Power Rule
dxd(xn)=nxn−1
dxd(sinu)
cosu⋅u′
dxd(cosu)
−sinu⋅u′
dxd(tanu)
sec2u⋅u′
dxd(cotu)
−csc2u⋅u′
dxd(secu)
secutanu⋅u′
dxd(cscu)
−cscucotu⋅u′
dxd(lnu)
uu′
dxd(eu)
eu⋅u′
dxd(u)
2uu′
dxd(sin−1u)
1−u2u′
dxd(cos−1u)
1−u2−u′
dxd(tan−1u)
1+u2u′
dxd(cot−1u)
1+u2−u′
Limit from the left
limx→c−f(x): the value f(x) approaches as x approaches c from below.
Limit from the right
limx→c+f(x): the value f(x) approaches as x approaches c from above.
Two-sided limit exists when
x→c−limf(x)=x→c+limf(x)
Limits fail to exist when
(1) left = right limit, (2) vertical asymptote, (3) oscillation (e.g., sin(1/x) near 0)
Definition of Continuity at x=c
f is continuous iff: (1) f(c) exists, (2) limx→cf(x) exists, (3) limx→cf(x)=f(c)
Derivatives fail to exist when
(1) not continuous, (2) sharp corner/cusp, (3) vertical tangent line
Intermediate Value Theorem (IVT)
If f is continuous on [a,b] and k is between f(a) and f(b), then ∃c∈(a,b) such that f(c)=k
Extreme Value Theorem (EVT)
If f is continuous on closed [a,b], then f has both an absolute maximum and minimum on that interval
L'Hopital's Rule
If limg(x)f(x) gives 00 or ∞∞, then limg(x)f(x)=limg′(x)f′(x)
x→0limxsinx
1
x→0limx1−cosx
0
x→0limxtanx
1
x→∞lim(1+x1)x
e