Essential for solving a wide range of calculus problems.
Differentiation Techniques
Product Rule: Used to differentiate the product of two functions.
If h(x)=f(x)g(x), then h′(x)=f′(x)g(x)+f(x)g′(x).
Quotient Rule: Used to differentiate the quotient of two functions.
If h(x)=g(x)f(x), then h′(x)=[g(x)]2f′(x)g(x)−f(x)g′(x).
Chain Rule: Used to differentiate composite functions.
If h(x)=f(g(x)), then h′(x)=f′(g(x))g′(x).
Integration Techniques
Substitution (u-substitution): Simplifies integrals by changing the variable.
Integration by Parts: Used to integrate the product of two functions.
∫udv=uv−∫vdu
Partial Fractions: Decomposes rational functions into simpler fractions for easier integration.
Mean Value Theorem
States that if a function f is continuous on the closed interval [a,b] and differentiable on the open interval (a,b), then there exists at least one point c in (a,b) such that f′(c)=b−af(b)−f(a).
Intermediate Value Theorem
States that if f is a continuous function on the closed interval [a,b], and k is any number between f(a) and f(b), then there exists at least one number c in the interval [a,b] such that f(c)=k.
Fundamental Theorem of Calculus
Part 1: If f is a continuous function on [a,x], then the derivative of the integral from a to x of f(t)dt is f(x).
dxd∫axf(t)dt=f(x)
Part 2: The definite integral of f(x) from a to b is the difference of the antiderivative F(x) evaluated at b and a.
∫abf(x)dx=F(b)−F(a)
L'Hopital's Rule
Used to evaluate limits of indeterminate forms (e.g., 00 or ∞∞).
If lim<em>x→cg(x)f(x) is of the form 00 or ∞∞, then lim</em>x→cg(x)f(x)=limx→cg′(x)f′(x), provided the limit exists.
Indeterminate Forms
Common indeterminate forms include 00, ∞∞, 0⋅∞, ∞−∞, 1∞, 00, and ∞0.
Techniques to handle: L'Hopital's Rule, algebraic manipulation, and rewriting expressions.
Rectangular Approximation and Trapezoidal Rule
Rectangular Approximation (Riemann Sum): Approximates the area under a curve using rectangles.
Trapezoidal Rule: Approximates the area under a curve using trapezoids.
∫<em>abf(x)dx≈2Δx[f(x</em>0)+2f(x<em>1)+2f(x</em>2)+⋯+2f(x<em>n−1)+f(x</em>n)] where Δx=nb−a
Volume Formulas
Disk Method: Used to find the volume of a solid of revolution when the slices are perpendicular to the axis of rotation and form disks.
V=π∫ab[r(x)]2dx
Washer Method: Similar to the disk method but used when there is a hole in the solid.
V=π∫ab([R(x)]2−[r(x)]2)dx
Shell Method: Used when the slices are parallel to the axis of rotation.
V=2π∫abr(x)h(x)dx
Average Value Formula
The average value of a function f(x) on the interval [a,b] is given by:
f<em>avg=b−a1∫</em>abf(x)dx
Euler's Method
A numerical method for approximating the solution of a differential equation.
Given dxdy=f(x,y) and an initial condition y(x<em>0)=y</em>0, the approximation is:
y<em>i+1=y</em>i+f(x<em>i,y</em>i)Δx
Differential Forms of Exponential and Logarithmic Functions
dxd(ex)=ex
dxd(ax)=axln(a)
dxd(lnx)=x1
dxd(logax)=xln(a)1
Sum of a Geometric Series
The sum of an infinite geometric series is given by:
S=1−ra, where a is the first term and r is the common ratio, and |r| < 1 for convergence.
Convergence/Divergence Tests
nth Term Test (Divergence Test): If lim<em>n→∞a</em>n=0, then the series ∑an diverges.
Geometric Series Test: A geometric series ∑arn converges if |r| < 1 and diverges if ∣r∣≥1.
Alternating Series Test: If an alternating series satisfies the conditions that the absolute value of the terms decreases monotonically and the limit of the terms is zero, then the series converges.
Integral Test: If f(x) is a positive, continuous, and decreasing function on [1,∞), then the series ∑<em>n=1∞f(n) and the integral ∫</em>1∞f(x)dx either both converge or both diverge.
Ratio Test: Let L=lim<em>n→∞∣ana</em>n+1∣; if L<1, the series converges; if L>1, the series diverges; if L=1, the test is inconclusive.
Direct Comparison Test: Compare the given series with a known convergent or divergent series.
Limit Comparison Test: If lim<em>n→∞b<em>na</em>n=c where c is a finite and positive number, then ∑a</em>n and ∑bn either both converge or both diverge.
Taylor Series Centered at x=a
The Taylor series of a function f(x) centered at x=a is given by:
∑n=0∞n!f(n)(a)(x−a)n
Lagrange Error Bound for Taylor Polynomials
The error in approximating f(x) by its nth degree Taylor polynomial Pn(x) is bounded by:
∣Rn(x)∣≤(n+1)!M∣x−a∣n+1, where M is the maximum value of ∣f(n+1)(z)∣ on the interval between a and x.