๐งฎ Arithmetic Formulas
Basic Operations
Order of Operations (PEMDAS/BODMAS)
Parentheses โ Exponents โ Multiplication/Division โ Addition/Subtraction
\( (a + b) \times c = ac + bc \)
\( (a + b) \times c = ac + bc \)
Example: \( 3 + 4 \times (2 + 5)^2 = 3 + 4 \times 49 = 3 + 196 = 199 \)
Insight: Multiplication and division have equal precedence, evaluated left to right.
Percentage Formulas
\( \text{Percentage} = \frac{\text{Part}}{\text{Whole}} \times 100\% \)
\( \text{Percentage Change} = \frac{\text{New - Old}}{\text{Old}} \times 100\% \)
\( \text{Compound Percentage: } A = P(1 + \frac{r}{100})^n \)
\( \text{Percentage Change} = \frac{\text{New - Old}}{\text{Old}} \times 100\% \)
\( \text{Compound Percentage: } A = P(1 + \frac{r}{100})^n \)
Example: 25% of 200 = \( \frac{25}{100} \times 200 = 50 \)
Fraction Operations
\( \frac{a}{b} + \frac{c}{d} = \frac{ad + bc}{bd} \)
\( \frac{a}{b} \times \frac{c}{d} = \frac{ac}{bd} \)
\( \frac{a}{b} \div \frac{c}{d} = \frac{a}{b} \times \frac{d}{c} \)
\( \frac{a}{b} \times \frac{c}{d} = \frac{ac}{bd} \)
\( \frac{a}{b} \div \frac{c}{d} = \frac{a}{b} \times \frac{d}{c} \)
Example: \( \frac{2}{3} + \frac{3}{4} = \frac{8 + 9}{12} = \frac{17}{12} \)
Exponents & Roots
Exponent Rules
\( a^m \times a^n = a^{m+n} \)
\( \frac{a^m}{a^n} = a^{m-n} \)
\( (a^m)^n = a^{mn} \)
\( a^{-n} = \frac{1}{a^n} \)
\( a^{1/n} = \sqrt[n]{a} \)
\( a^0 = 1 \ (a \neq 0) \)
\( \frac{a^m}{a^n} = a^{m-n} \)
\( (a^m)^n = a^{mn} \)
\( a^{-n} = \frac{1}{a^n} \)
\( a^{1/n} = \sqrt[n]{a} \)
\( a^0 = 1 \ (a \neq 0) \)
Radical Properties
\( \sqrt[n]{ab} = \sqrt[n]{a} \times \sqrt[n]{b} \)
\( \sqrt[n]{\frac{a}{b}} = \frac{\sqrt[n]{a}}{\sqrt[n]{b}} \)
\( \sqrt[m]{\sqrt[n]{a}} = \sqrt[mn]{a} \)
\( a^{m/n} = \sqrt[n]{a^m} = (\sqrt[n]{a})^m \)
\( \sqrt[n]{\frac{a}{b}} = \frac{\sqrt[n]{a}}{\sqrt[n]{b}} \)
\( \sqrt[m]{\sqrt[n]{a}} = \sqrt[mn]{a} \)
\( a^{m/n} = \sqrt[n]{a^m} = (\sqrt[n]{a})^m \)
Logarithm Properties
\( \log_b(xy) = \log_b x + \log_b y \)
\( \log_b(\frac{x}{y}) = \log_b x - \log_b y \)
\( \log_b(x^n) = n \log_b x \)
\( \log_b a = \frac{\log_c a}{\log_c b} \) (Change of base)
\( b^{\log_b x} = x \)
\( \log_b(\frac{x}{y}) = \log_b x - \log_b y \)
\( \log_b(x^n) = n \log_b x \)
\( \log_b a = \frac{\log_c a}{\log_c b} \) (Change of base)
\( b^{\log_b x} = x \)
Sequences & Series
Arithmetic Sequence
\( a_n = a_1 + (n-1)d \)
\( S_n = \frac{n}{2}[2a_1 + (n-1)d] = \frac{n}{2}(a_1 + a_n) \)
\( S_n = \frac{n}{2}[2a_1 + (n-1)d] = \frac{n}{2}(a_1 + a_n) \)
Geometric Sequence
\( a_n = a_1 r^{n-1} \)
\( S_n = \frac{a_1(1 - r^n)}{1 - r} \ (r \neq 1) \)
\( S_\infty = \frac{a_1}{1 - r} \ (|r| < 1) \)
\( S_n = \frac{a_1(1 - r^n)}{1 - r} \ (r \neq 1) \)
\( S_\infty = \frac{a_1}{1 - r} \ (|r| < 1) \)
Special Series
\( \sum_{k=1}^n k = \frac{n(n+1)}{2} \)
\( \sum_{k=1}^n k^2 = \frac{n(n+1)(2n+1)}{6} \)
\( \sum_{k=1}^n k^3 = \left[\frac{n(n+1)}{2}\right]^2 \)
\( \sum_{k=1}^n k^2 = \frac{n(n+1)(2n+1)}{6} \)
\( \sum_{k=1}^n k^3 = \left[\frac{n(n+1)}{2}\right]^2 \)
๐ Algebra Formulas
Quadratic Equations
Quadratic Formula
\( ax^2 + bx + c = 0 \)
\( x = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a} \)
Discriminant: \( \Delta = b^2 - 4ac \)
\( x = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a} \)
Discriminant: \( \Delta = b^2 - 4ac \)
Insight: If ฮ > 0: two real roots, ฮ = 0: one real root, ฮ < 0: two complex roots
Vieta's Formulas
For \( ax^2 + bx + c = 0 \) with roots ฮฑ, ฮฒ:
\( \alpha + \beta = -\frac{b}{a} \)
\( \alpha\beta = \frac{c}{a} \)
\( \alpha + \beta = -\frac{b}{a} \)
\( \alpha\beta = \frac{c}{a} \)
Completing the Square
\( ax^2 + bx + c = a\left(x + \frac{b}{2a}\right)^2 + \left(c - \frac{b^2}{4a}\right) \)
Factoring Formulas
Basic Identities
\( a^2 - b^2 = (a-b)(a+b) \)
\( a^2 + 2ab + b^2 = (a+b)^2 \)
\( a^2 - 2ab + b^2 = (a-b)^2 \)
\( a^3 + b^3 = (a+b)(a^2 - ab + b^2) \)
\( a^3 - b^3 = (a-b)(a^2 + ab + b^2) \)
\( a^2 + 2ab + b^2 = (a+b)^2 \)
\( a^2 - 2ab + b^2 = (a-b)^2 \)
\( a^3 + b^3 = (a+b)(a^2 - ab + b^2) \)
\( a^3 - b^3 = (a-b)(a^2 + ab + b^2) \)
Advanced Factoring
\( a^4 + b^4 = (a^2 + \sqrt{2}ab + b^2)(a^2 - \sqrt{2}ab + b^2) \)
\( a^n - b^n = (a-b)(a^{n-1} + a^{n-2}b + \dots + b^{n-1}) \)
\( a^n + b^n = (a+b)(a^{n-1} - a^{n-2}b + \dots - ab^{n-2} + b^{n-1}) \) (n odd)
\( a^n - b^n = (a-b)(a^{n-1} + a^{n-2}b + \dots + b^{n-1}) \)
\( a^n + b^n = (a+b)(a^{n-1} - a^{n-2}b + \dots - ab^{n-2} + b^{n-1}) \) (n odd)
Polynomials
Binomial Theorem
\( (a+b)^n = \sum_{k=0}^{n} \binom{n}{k} a^{n-k} b^k \)
\( \binom{n}{k} = \frac{n!}{k!(n-k)!} \)
\( \binom{n}{k} = \frac{n!}{k!(n-k)!} \)
Polynomial Roots
For \( P(x) = a_nx^n + a_{n-1}x^{n-1} + \dots + a_0 \):
Sum of roots: \( -\frac{a_{n-1}}{a_n} \)
Product of roots: \( (-1)^n \frac{a_0}{a_n} \)
Sum of roots: \( -\frac{a_{n-1}}{a_n} \)
Product of roots: \( (-1)^n \frac{a_0}{a_n} \)
Synthetic Division
For dividing by \( (x-c) \):
Bring down leading coefficient, multiply by c, add to next coefficient
Bring down leading coefficient, multiply by c, add to next coefficient
Systems of Equations
Cramer's Rule
For \( ax + by = e \), \( cx + dy = f \):
\( x = \frac{\begin{vmatrix} e & b \\ f & d \end{vmatrix}}{\begin{vmatrix} a & b \\ c & d \end{vmatrix}} \),
\( y = \frac{\begin{vmatrix} a & e \\ c & f \end{vmatrix}}{\begin{vmatrix} a & b \\ c & d \end{vmatrix}} \)
\( x = \frac{\begin{vmatrix} e & b \\ f & d \end{vmatrix}}{\begin{vmatrix} a & b \\ c & d \end{vmatrix}} \),
\( y = \frac{\begin{vmatrix} a & e \\ c & f \end{vmatrix}}{\begin{vmatrix} a & b \\ c & d \end{vmatrix}} \)
๐บ Geometry Formulas
Plane Geometry
Pythagorean Theorem
\( a^2 + b^2 = c^2 \)
Generalized: \( \cos C = \frac{a^2 + b^2 - c^2}{2ab} \)
Generalized: \( \cos C = \frac{a^2 + b^2 - c^2}{2ab} \)
Area Formulas
Triangle: \( A = \frac{1}{2}bh = \frac{1}{2}ab\sin C \)
Rectangle: \( A = lw \)
Circle: \( A = \pi r^2 \)
Trapezoid: \( A = \frac{1}{2}(a+b)h \)
Parallelogram: \( A = bh \)
Rectangle: \( A = lw \)
Circle: \( A = \pi r^2 \)
Trapezoid: \( A = \frac{1}{2}(a+b)h \)
Parallelogram: \( A = bh \)
Perimeter/Circumference
Circle: \( C = 2\pi r = \pi d \)
Rectangle: \( P = 2(l + w) \)
Triangle: \( P = a + b + c \)
Rectangle: \( P = 2(l + w) \)
Triangle: \( P = a + b + c \)
Solid Geometry
Volume Formulas
Cube: \( V = s^3 \)
Rectangular Prism: \( V = lwh \)
Sphere: \( V = \frac{4}{3}\pi r^3 \)
Cylinder: \( V = \pi r^2 h \)
Cone: \( V = \frac{1}{3}\pi r^2 h \)
Pyramid: \( V = \frac{1}{3}Bh \)
Rectangular Prism: \( V = lwh \)
Sphere: \( V = \frac{4}{3}\pi r^3 \)
Cylinder: \( V = \pi r^2 h \)
Cone: \( V = \frac{1}{3}\pi r^2 h \)
Pyramid: \( V = \frac{1}{3}Bh \)
Surface Area
Sphere: \( SA = 4\pi r^2 \)
Cylinder: \( SA = 2\pi r(h + r) \)
Cone: \( SA = \pi r(r + \sqrt{h^2 + r^2}) \)
Cube: \( SA = 6s^2 \)
Cylinder: \( SA = 2\pi r(h + r) \)
Cone: \( SA = \pi r(r + \sqrt{h^2 + r^2}) \)
Cube: \( SA = 6s^2 \)
Analytic Geometry
Distance Formulas
2D: \( d = \sqrt{(x_2-x_1)^2 + (y_2-y_1)^2} \)
3D: \( d = \sqrt{(x_2-x_1)^2 + (y_2-y_1)^2 + (z_2-z_1)^2} \)
Point to line: \( d = \frac{|Ax_0 + By_0 + C|}{\sqrt{A^2 + B^2}} \)
3D: \( d = \sqrt{(x_2-x_1)^2 + (y_2-y_1)^2 + (z_2-z_1)^2} \)
Point to line: \( d = \frac{|Ax_0 + By_0 + C|}{\sqrt{A^2 + B^2}} \)
Line Equations
Slope-intercept: \( y = mx + b \)
Point-slope: \( y - y_1 = m(x - x_1) \)
Two-point: \( \frac{y - y_1}{y_2 - y_1} = \frac{x - x_1}{x_2 - x_1} \)
General: \( Ax + By + C = 0 \)
Point-slope: \( y - y_1 = m(x - x_1) \)
Two-point: \( \frac{y - y_1}{y_2 - y_1} = \frac{x - x_1}{x_2 - x_1} \)
General: \( Ax + By + C = 0 \)
Circle Equations
Standard: \( (x-h)^2 + (y-k)^2 = r^2 \)
General: \( x^2 + y^2 + Dx + Ey + F = 0 \)
Parametric: \( x = h + r\cos\theta, y = k + r\sin\theta \)
General: \( x^2 + y^2 + Dx + Ey + F = 0 \)
Parametric: \( x = h + r\cos\theta, y = k + r\sin\theta \)
Trigonometry in Geometry
Law of Sines & Cosines
Law of Sines: \( \frac{a}{\sin A} = \frac{b}{\sin B} = \frac{c}{\sin C} \)
Law of Cosines: \( c^2 = a^2 + b^2 - 2ab\cos C \)
Law of Cosines: \( c^2 = a^2 + b^2 - 2ab\cos C \)
Area using Trigonometry
\( A = \frac{1}{2}ab\sin C \)
Heron's: \( A = \sqrt{s(s-a)(s-b)(s-c)} \), \( s = \frac{a+b+c}{2} \)
Heron's: \( A = \sqrt{s(s-a)(s-b)(s-c)} \), \( s = \frac{a+b+c}{2} \)
โ Calculus Formulas
Derivatives
Basic Derivative Rules
\( \frac{d}{dx}(c) = 0 \)
\( \frac{d}{dx}(x^n) = nx^{n-1} \)
\( \frac{d}{dx}(e^x) = e^x \)
\( \frac{d}{dx}(a^x) = a^x \ln a \)
\( \frac{d}{dx}(\ln x) = \frac{1}{x} \)
\( \frac{d}{dx}(\log_a x) = \frac{1}{x \ln a} \)
\( \frac{d}{dx}(x^n) = nx^{n-1} \)
\( \frac{d}{dx}(e^x) = e^x \)
\( \frac{d}{dx}(a^x) = a^x \ln a \)
\( \frac{d}{dx}(\ln x) = \frac{1}{x} \)
\( \frac{d}{dx}(\log_a x) = \frac{1}{x \ln a} \)
Trigonometric Derivatives
\( \frac{d}{dx}(\sin x) = \cos x \)
\( \frac{d}{dx}(\cos x) = -\sin x \)
\( \frac{d}{dx}(\tan x) = \sec^2 x \)
\( \frac{d}{dx}(\cot x) = -\csc^2 x \)
\( \frac{d}{dx}(\sec x) = \sec x \tan x \)
\( \frac{d}{dx}(\csc x) = -\csc x \cot x \)
\( \frac{d}{dx}(\cos x) = -\sin x \)
\( \frac{d}{dx}(\tan x) = \sec^2 x \)
\( \frac{d}{dx}(\cot x) = -\csc^2 x \)
\( \frac{d}{dx}(\sec x) = \sec x \tan x \)
\( \frac{d}{dx}(\csc x) = -\csc x \cot x \)
Inverse Trig Derivatives
\( \frac{d}{dx}(\sin^{-1} x) = \frac{1}{\sqrt{1-x^2}} \)
\( \frac{d}{dx}(\cos^{-1} x) = -\frac{1}{\sqrt{1-x^2}} \)
\( \frac{d}{dx}(\tan^{-1} x) = \frac{1}{1+x^2} \)
\( \frac{d}{dx}(\cos^{-1} x) = -\frac{1}{\sqrt{1-x^2}} \)
\( \frac{d}{dx}(\tan^{-1} x) = \frac{1}{1+x^2} \)
Derivative Rules
Product: \( (fg)' = f'g + fg' \)
Quotient: \( \left(\frac{f}{g}\right)' = \frac{f'g - fg'}{g^2} \)
Chain: \( (f(g(x)))' = f'(g(x)) \cdot g'(x) \)
Implicit: \( \frac{dy}{dx} = -\frac{F_x}{F_y} \)
Quotient: \( \left(\frac{f}{g}\right)' = \frac{f'g - fg'}{g^2} \)
Chain: \( (f(g(x)))' = f'(g(x)) \cdot g'(x) \)
Implicit: \( \frac{dy}{dx} = -\frac{F_x}{F_y} \)
Integrals
Basic Integrals
\( \int x^n dx = \frac{x^{n+1}}{n+1} + C \ (n \neq -1) \)
\( \int \frac{1}{x} dx = \ln|x| + C \)
\( \int e^x dx = e^x + C \)
\( \int a^x dx = \frac{a^x}{\ln a} + C \)
\( \int \frac{1}{x} dx = \ln|x| + C \)
\( \int e^x dx = e^x + C \)
\( \int a^x dx = \frac{a^x}{\ln a} + C \)
Trigonometric Integrals
\( \int \sin x dx = -\cos x + C \)
\( \int \cos x dx = \sin x + C \)
\( \int \sec^2 x dx = \tan x + C \)
\( \int \csc^2 x dx = -\cot x + C \)
\( \int \cos x dx = \sin x + C \)
\( \int \sec^2 x dx = \tan x + C \)
\( \int \csc^2 x dx = -\cot x + C \)
Integration Techniques
Substitution: \( \int f(g(x))g'(x)dx = \int f(u)du \)
Parts: \( \int u dv = uv - \int v du \)
Partial Fractions: \( \int \frac{P(x)}{Q(x)}dx \)
Trig Sub: \( x = a\sin\theta, a\tan\theta, a\sec\theta \)
Parts: \( \int u dv = uv - \int v du \)
Partial Fractions: \( \int \frac{P(x)}{Q(x)}dx \)
Trig Sub: \( x = a\sin\theta, a\tan\theta, a\sec\theta \)
Definite Integrals
\( \int_a^b f(x)dx = F(b) - F(a) \)
\( \int_a^b f(x)dx = -\int_b^a f(x)dx \)
\( \int_a^b [f(x) \pm g(x)]dx = \int_a^b f(x)dx \pm \int_a^b g(x)dx \)
\( \int_a^b f(x)dx = -\int_b^a f(x)dx \)
\( \int_a^b [f(x) \pm g(x)]dx = \int_a^b f(x)dx \pm \int_a^b g(x)dx \)
Series & Sequences
Taylor Series
\( f(x) = \sum_{n=0}^\infty \frac{f^{(n)}(a)}{n!}(x-a)^n \)
Maclaurin (a=0): \( f(x) = \sum_{n=0}^\infty \frac{f^{(n)}(0)}{n!}x^n \)
Maclaurin (a=0): \( f(x) = \sum_{n=0}^\infty \frac{f^{(n)}(0)}{n!}x^n \)
Common Series
\( e^x = \sum_{n=0}^\infty \frac{x^n}{n!} \)
\( \sin x = \sum_{n=0}^\infty \frac{(-1)^n x^{2n+1}}{(2n+1)!} \)
\( \cos x = \sum_{n=0}^\infty \frac{(-1)^n x^{2n}}{(2n)!} \)
\( \ln(1+x) = \sum_{n=1}^\infty \frac{(-1)^{n+1} x^n}{n} \)
\( \sin x = \sum_{n=0}^\infty \frac{(-1)^n x^{2n+1}}{(2n+1)!} \)
\( \cos x = \sum_{n=0}^\infty \frac{(-1)^n x^{2n}}{(2n)!} \)
\( \ln(1+x) = \sum_{n=1}^\infty \frac{(-1)^{n+1} x^n}{n} \)
Multivariable Calculus
Partial Derivatives
\( f_x = \frac{\partial f}{\partial x} \)
\( f_{xy} = \frac{\partial^2 f}{\partial y \partial x} \)
Chain: \( \frac{dz}{dt} = \frac{\partial z}{\partial x}\frac{dx}{dt} + \frac{\partial z}{\partial y}\frac{dy}{dt} \)
\( f_{xy} = \frac{\partial^2 f}{\partial y \partial x} \)
Chain: \( \frac{dz}{dt} = \frac{\partial z}{\partial x}\frac{dx}{dt} + \frac{\partial z}{\partial y}\frac{dy}{dt} \)
Gradient & Directional Derivative
\( \nabla f = \left\langle \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y} \right\rangle \)
\( D_{\vec{u}} f = \nabla f \cdot \vec{u} \)
\( D_{\vec{u}} f = \nabla f \cdot \vec{u} \)
Multiple Integrals
Double: \( \iint_R f(x,y) dA \)
Triple: \( \iiint_E f(x,y,z) dV \)
Polar: \( \iint f(r,\theta) r dr d\theta \)
Triple: \( \iiint_E f(x,y,z) dV \)
Polar: \( \iint f(r,\theta) r dr d\theta \)
๐ Statistics Formulas
Descriptive Statistics
Measures of Center
Mean: \( \mu = \frac{\sum x_i}{N} \) (population)
Sample Mean: \( \bar{x} = \frac{\sum x_i}{n} \)
Median: middle value when sorted
Mode: most frequent value
Sample Mean: \( \bar{x} = \frac{\sum x_i}{n} \)
Median: middle value when sorted
Mode: most frequent value
Measures of Spread
Variance: \( \sigma^2 = \frac{\sum (x_i - \mu)^2}{N} \)
Sample Variance: \( s^2 = \frac{\sum (x_i - \bar{x})^2}{n-1} \)
Standard Deviation: \( \sigma = \sqrt{\sigma^2} \)
Range: \( \max - \min \)
Sample Variance: \( s^2 = \frac{\sum (x_i - \bar{x})^2}{n-1} \)
Standard Deviation: \( \sigma = \sqrt{\sigma^2} \)
Range: \( \max - \min \)
Percentiles & Quartiles
Q1: 25th percentile
Q2: 50th percentile (median)
Q3: 75th percentile
IQR: \( Q3 - Q1 \)
Q2: 50th percentile (median)
Q3: 75th percentile
IQR: \( Q3 - Q1 \)
Probability Distributions
Discrete Distributions
Binomial: \( P(X=k) = \binom{n}{k} p^k (1-p)^{n-k} \)
Poisson: \( P(X=k) = \frac{\lambda^k e^{-\lambda}}{k!} \)
Geometric: \( P(X=k) = (1-p)^{k-1}p \)
Poisson: \( P(X=k) = \frac{\lambda^k e^{-\lambda}}{k!} \)
Geometric: \( P(X=k) = (1-p)^{k-1}p \)
Continuous Distributions
Normal: \( f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x-\mu)^2}{2\sigma^2}} \)
Exponential: \( f(x) = \lambda e^{-\lambda x} \)
Uniform: \( f(x) = \frac{1}{b-a} \)
Exponential: \( f(x) = \lambda e^{-\lambda x} \)
Uniform: \( f(x) = \frac{1}{b-a} \)
Inferential Statistics
Confidence Intervals
Mean CI: \( \bar{x} \pm z_{\alpha/2} \frac{\sigma}{\sqrt{n}} \)
Proportion CI: \( \hat{p} \pm z_{\alpha/2} \sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \)
t-interval: \( \bar{x} \pm t_{\alpha/2} \frac{s}{\sqrt{n}} \)
Proportion CI: \( \hat{p} \pm z_{\alpha/2} \sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \)
t-interval: \( \bar{x} \pm t_{\alpha/2} \frac{s}{\sqrt{n}} \)
Hypothesis Testing
z-test: \( z = \frac{\bar{x} - \mu}{\sigma/\sqrt{n}} \)
t-test: \( t = \frac{\bar{x} - \mu}{s/\sqrt{n}} \)
Chi-square: \( \chi^2 = \sum \frac{(O-E)^2}{E} \)
t-test: \( t = \frac{\bar{x} - \mu}{s/\sqrt{n}} \)
Chi-square: \( \chi^2 = \sum \frac{(O-E)^2}{E} \)
Regression & Correlation
Linear Regression
\( y = \beta_0 + \beta_1 x + \epsilon \)
\( \hat{\beta}_1 = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2} \)
\( \hat{\beta}_0 = \bar{y} - \hat{\beta}_1 \bar{x} \)
\( \hat{\beta}_1 = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2} \)
\( \hat{\beta}_0 = \bar{y} - \hat{\beta}_1 \bar{x} \)
Correlation
Pearson's r: \( r = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum (x_i - \bar{x})^2 \sum (y_i - \bar{y})^2}} \)
Rยฒ: coefficient of determination
Rยฒ: coefficient of determination
Trigonometry Formulas
Basic Identities
Pythagorean Identities
\( \sin^2\theta + \cos^2\theta = 1 \)
\( 1 + \tan^2\theta = \sec^2\theta \)
\( 1 + \cot^2\theta = \csc^2\theta \)
\( 1 + \tan^2\theta = \sec^2\theta \)
\( 1 + \cot^2\theta = \csc^2\theta \)
Angle Sum & Difference
\( \sin(A \pm B) = \sin A \cos B \pm \cos A \sin B \)
\( \cos(A \pm B) = \cos A \cos B \mp \sin A \sin B \)
\( \tan(A \pm B) = \frac{\tan A \pm \tan B}{1 \mp \tan A \tan B} \)
\( \cos(A \pm B) = \cos A \cos B \mp \sin A \sin B \)
\( \tan(A \pm B) = \frac{\tan A \pm \tan B}{1 \mp \tan A \tan B} \)
Double & Half Angles
\( \sin 2\theta = 2\sin\theta\cos\theta \)
\( \cos 2\theta = \cos^2\theta - \sin^2\theta = 2\cos^2\theta - 1 = 1 - 2\sin^2\theta \)
\( \tan 2\theta = \frac{2\tan\theta}{1 - \tan^2\theta} \)
\( \sin\frac{\theta}{2} = \pm\sqrt{\frac{1 - \cos\theta}{2}} \)
\( \cos\frac{\theta}{2} = \pm\sqrt{\frac{1 + \cos\theta}{2}} \)
\( \cos 2\theta = \cos^2\theta - \sin^2\theta = 2\cos^2\theta - 1 = 1 - 2\sin^2\theta \)
\( \tan 2\theta = \frac{2\tan\theta}{1 - \tan^2\theta} \)
\( \sin\frac{\theta}{2} = \pm\sqrt{\frac{1 - \cos\theta}{2}} \)
\( \cos\frac{\theta}{2} = \pm\sqrt{\frac{1 + \cos\theta}{2}} \)
Product-to-Sum & Sum-to-Product
Product-to-Sum
\( \sin A \cos B = \frac{1}{2}[\sin(A+B) + \sin(A-B)] \)
\( \cos A \cos B = \frac{1}{2}[\cos(A+B) + \cos(A-B)] \)
\( \sin A \sin B = \frac{1}{2}[\cos(A-B) - \cos(A+B)] \)
\( \cos A \cos B = \frac{1}{2}[\cos(A+B) + \cos(A-B)] \)
\( \sin A \sin B = \frac{1}{2}[\cos(A-B) - \cos(A+B)] \)
Sum-to-Product
\( \sin A + \sin B = 2\sin\left(\frac{A+B}{2}\right)\cos\left(\frac{A-B}{2}\right) \)
\( \sin A - \sin B = 2\cos\left(\frac{A+B}{2}\right)\sin\left(\frac{A-B}{2}\right) \)
\( \cos A + \cos B = 2\cos\left(\frac{A+B}{2}\right)\cos\left(\frac{A-B}{2}\right) \)
\( \cos A - \cos B = -2\sin\left(\frac{A+B}{2}\right)\sin\left(\frac{A-B}{2}\right) \)
\( \sin A - \sin B = 2\cos\left(\frac{A+B}{2}\right)\sin\left(\frac{A-B}{2}\right) \)
\( \cos A + \cos B = 2\cos\left(\frac{A+B}{2}\right)\cos\left(\frac{A-B}{2}\right) \)
\( \cos A - \cos B = -2\sin\left(\frac{A+B}{2}\right)\sin\left(\frac{A-B}{2}\right) \)
Trigonometric Equations
General Solutions
\( \sin\theta = \sin\alpha \Rightarrow \theta = n\pi + (-1)^n\alpha \)
\( \cos\theta = \cos\alpha \Rightarrow \theta = 2n\pi \pm \alpha \)
\( \tan\theta = \tan\alpha \Rightarrow \theta = n\pi + \alpha \)
\( \cos\theta = \cos\alpha \Rightarrow \theta = 2n\pi \pm \alpha \)
\( \tan\theta = \tan\alpha \Rightarrow \theta = n\pi + \alpha \)
Inverse Trigonometry
Principal Values
\( \sin^{-1}x \in [-\frac{\pi}{2}, \frac{\pi}{2}] \)
\( \cos^{-1}x \in [0, \pi] \)
\( \tan^{-1}x \in (-\frac{\pi}{2}, \frac{\pi}{2}) \)
\( \cos^{-1}x \in [0, \pi] \)
\( \tan^{-1}x \in (-\frac{\pi}{2}, \frac{\pi}{2}) \)
Inverse Identities
\( \sin^{-1}x + \cos^{-1}x = \frac{\pi}{2} \)
\( \tan^{-1}x + \cot^{-1}x = \frac{\pi}{2} \)
\( \sec^{-1}x + \csc^{-1}x = \frac{\pi}{2} \)
\( \tan^{-1}x + \cot^{-1}x = \frac{\pi}{2} \)
\( \sec^{-1}x + \csc^{-1}x = \frac{\pi}{2} \)
Number Theory Formulas
Divisibility & Primes
Divisibility Rules
Divisible by 2: last digit even
Divisible by 3: sum of digits divisible by 3
Divisible by 4: last two digits divisible by 4
Divisible by 5: ends with 0 or 5
Divisible by 6: divisible by 2 and 3
Divisible by 9: sum of digits divisible by 9
Divisible by 3: sum of digits divisible by 3
Divisible by 4: last two digits divisible by 4
Divisible by 5: ends with 0 or 5
Divisible by 6: divisible by 2 and 3
Divisible by 9: sum of digits divisible by 9
Prime Formulas
Prime Counting: \( \pi(x) \sim \frac{x}{\ln x} \)
Prime Factorization: \( n = p_1^{a_1} p_2^{a_2} \dots p_k^{a_k} \)
Number of divisors: \( d(n) = (a_1+1)(a_2+1)\dots(a_k+1) \)
Prime Factorization: \( n = p_1^{a_1} p_2^{a_2} \dots p_k^{a_k} \)
Number of divisors: \( d(n) = (a_1+1)(a_2+1)\dots(a_k+1) \)
Modular Arithmetic
Modulo Operations
\( a \equiv b \pmod{m} \iff m \mid (a-b) \)
\( (a+b) \mod m = ((a \mod m) + (b \mod m)) \mod m \)
\( (ab) \mod m = ((a \mod m)(b \mod m)) \mod m \)
\( (a+b) \mod m = ((a \mod m) + (b \mod m)) \mod m \)
\( (ab) \mod m = ((a \mod m)(b \mod m)) \mod m \)
Fermat's & Euler's Theorems
Fermat: \( a^{p-1} \equiv 1 \pmod{p} \) (p prime, a not divisible by p)
Euler: \( a^{\phi(n)} \equiv 1 \pmod{n} \) (gcd(a,n)=1)
\( \phi(n) = n \prod_{p|n}(1 - \frac{1}{p}) \)
Euler: \( a^{\phi(n)} \equiv 1 \pmod{n} \) (gcd(a,n)=1)
\( \phi(n) = n \prod_{p|n}(1 - \frac{1}{p}) \)
GCD & LCM
Euclidean Algorithm
\( \gcd(a,b) = \gcd(b, a \mod b) \)
Extended: \( ax + by = \gcd(a,b) \)
\( \text{lcm}(a,b) = \frac{ab}{\gcd(a,b)} \)
Extended: \( ax + by = \gcd(a,b) \)
\( \text{lcm}(a,b) = \frac{ab}{\gcd(a,b)} \)
Linear Algebra Formulas
Matrix Operations
Matrix Multiplication
\( (AB)_{ij} = \sum_{k=1}^n A_{ik}B_{kj} \)
\( A(BC) = (AB)C \)
\( A(B+C) = AB + AC \)
\( A(BC) = (AB)C \)
\( A(B+C) = AB + AC \)
Determinants
2ร2: \( \begin{vmatrix} a & b \\ c & d \end{vmatrix} = ad - bc \)
3ร3: Sarrus' rule or cofactor expansion
\( \det(AB) = \det(A)\det(B) \)
\( \det(A^{-1}) = \frac{1}{\det(A)} \)
3ร3: Sarrus' rule or cofactor expansion
\( \det(AB) = \det(A)\det(B) \)
\( \det(A^{-1}) = \frac{1}{\det(A)} \)
Inverse Matrix
2ร2: \( A^{-1} = \frac{1}{ad-bc} \begin{pmatrix} d & -b \\ -c & a \end{pmatrix} \)
\( AA^{-1} = A^{-1}A = I \)
\( (AB)^{-1} = B^{-1}A^{-1} \)
\( AA^{-1} = A^{-1}A = I \)
\( (AB)^{-1} = B^{-1}A^{-1} \)
Vector Spaces
Vector Operations
Dot product: \( \vec{a} \cdot \vec{b} = \sum a_i b_i = |a||b|\cos\theta \)
Cross product (3D): \( \vec{a} \times \vec{b} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \end{vmatrix} \)
Magnitude: \( |\vec{a}| = \sqrt{\sum a_i^2} \)
Cross product (3D): \( \vec{a} \times \vec{b} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \end{vmatrix} \)
Magnitude: \( |\vec{a}| = \sqrt{\sum a_i^2} \)
Linear Independence
Vectors linearly independent if \( c_1\vec{v}_1 + \dots + c_n\vec{v}_n = 0 \) implies all \( c_i = 0 \)
Rank: dimension of column space
Nullity: dimension of null space
Rank: dimension of column space
Nullity: dimension of null space
Eigenvalues & Eigenvectors
Characteristic Equation
\( \det(A - \lambda I) = 0 \)
For 2ร2: \( \lambda^2 - \text{tr}(A)\lambda + \det(A) = 0 \)
\( A\vec{v} = \lambda\vec{v} \)
For 2ร2: \( \lambda^2 - \text{tr}(A)\lambda + \det(A) = 0 \)
\( A\vec{v} = \lambda\vec{v} \)
Diagonalization
\( A = PDP^{-1} \) where D diagonal, P eigenvectors
\( A^n = PD^nP^{-1} \)
\( A^n = PD^nP^{-1} \)
Differential Equations Formulas
First Order ODEs
Separable Equations
\( \frac{dy}{dx} = f(x)g(y) \)
Solution: \( \int \frac{dy}{g(y)} = \int f(x)dx + C \)
Solution: \( \int \frac{dy}{g(y)} = \int f(x)dx + C \)
Linear First Order
\( \frac{dy}{dx} + P(x)y = Q(x) \)
Integrating factor: \( \mu(x) = e^{\int P(x)dx} \)
Solution: \( y = \frac{1}{\mu(x)}\int \mu(x)Q(x)dx + \frac{C}{\mu(x)} \)
Integrating factor: \( \mu(x) = e^{\int P(x)dx} \)
Solution: \( y = \frac{1}{\mu(x)}\int \mu(x)Q(x)dx + \frac{C}{\mu(x)} \)
Exact Equations
\( M(x,y)dx + N(x,y)dy = 0 \) exact if \( \frac{\partial M}{\partial y} = \frac{\partial N}{\partial x} \)
Solution: \( \int M dx + \int (N - \frac{\partial}{\partial y}\int M dx)dy = C \)
Solution: \( \int M dx + \int (N - \frac{\partial}{\partial y}\int M dx)dy = C \)
Second Order Linear ODEs
Constant Coefficients
\( ay'' + by' + cy = 0 \)
Characteristic: \( ar^2 + br + c = 0 \)
Real distinct roots: \( y = C_1e^{r_1x} + C_2e^{r_2x} \)
Real repeated: \( y = (C_1 + C_2x)e^{rx} \)
Complex: \( y = e^{\alpha x}(C_1\cos\beta x + C_2\sin\beta x) \)
Characteristic: \( ar^2 + br + c = 0 \)
Real distinct roots: \( y = C_1e^{r_1x} + C_2e^{r_2x} \)
Real repeated: \( y = (C_1 + C_2x)e^{rx} \)
Complex: \( y = e^{\alpha x}(C_1\cos\beta x + C_2\sin\beta x) \)
Non-homogeneous
\( ay'' + by' + cy = f(x) \)
General solution: \( y = y_h + y_p \)
Method of undetermined coefficients
Variation of parameters
General solution: \( y = y_h + y_p \)
Method of undetermined coefficients
Variation of parameters
Special Equations
Cauchy-Euler Equation
\( ax^2y'' + bxy' + cy = 0 \)
Assume \( y = x^r \), solve \( ar(r-1) + br + c = 0 \)
Assume \( y = x^r \), solve \( ar(r-1) + br + c = 0 \)
Bernoulli Equation
\( y' + P(x)y = Q(x)y^n \)
Substitute \( v = y^{1-n} \)
Substitute \( v = y^{1-n} \)
Probability Formulas
Basic Probability
Probability Rules
\( P(A \cup B) = P(A) + P(B) - P(A \cap B) \)
\( P(A^c) = 1 - P(A) \)
\( P(A|B) = \frac{P(A \cap B)}{P(B)} \)
\( P(A \cap B) = P(A)P(B|A) \)
\( P(A^c) = 1 - P(A) \)
\( P(A|B) = \frac{P(A \cap B)}{P(B)} \)
\( P(A \cap B) = P(A)P(B|A) \)
Bayes' Theorem
\( P(A|B) = \frac{P(B|A)P(A)}{P(B)} \)
\( P(B) = P(B|A)P(A) + P(B|A^c)P(A^c) \)
\( P(B) = P(B|A)P(A) + P(B|A^c)P(A^c) \)
Independence
\( A \) and \( B \) independent if \( P(A \cap B) = P(A)P(B) \)
\( P(A|B) = P(A) \) if independent
\( P(A|B) = P(A) \) if independent
Random Variables
Expectation & Variance
\( E[X] = \sum x_i p_i \) (discrete)
\( E[X] = \int_{-\infty}^{\infty} x f(x) dx \) (continuous)
\( \text{Var}(X) = E[(X-\mu)^2] = E[X^2] - (E[X])^2 \)
\( \text{SD}(X) = \sqrt{\text{Var}(X)} \)
\( E[X] = \int_{-\infty}^{\infty} x f(x) dx \) (continuous)
\( \text{Var}(X) = E[(X-\mu)^2] = E[X^2] - (E[X])^2 \)
\( \text{SD}(X) = \sqrt{\text{Var}(X)} \)
Moment Generating Functions
\( M_X(t) = E[e^{tX}] \)
\( E[X^n] = M_X^{(n)}(0) \)
\( E[X^n] = M_X^{(n)}(0) \)
Limit Theorems
Law of Large Numbers
Weak: \( \frac{1}{n}\sum_{i=1}^n X_i \xrightarrow{P} \mu \)
Strong: \( \frac{1}{n}\sum_{i=1}^n X_i \xrightarrow{a.s.} \mu \)
Strong: \( \frac{1}{n}\sum_{i=1}^n X_i \xrightarrow{a.s.} \mu \)
Central Limit Theorem
\( \frac{\bar{X} - \mu}{\sigma/\sqrt{n}} \xrightarrow{d} N(0,1) \)
Complex Analysis Formulas
Complex Numbers
Forms & Operations
Rectangular: \( z = x + iy \)
Polar: \( z = r(\cos\theta + i\sin\theta) = re^{i\theta} \)
Multiplication: \( r_1e^{i\theta_1} \cdot r_2e^{i\theta_2} = r_1r_2e^{i(\theta_1+\theta_2)} \)
De Moivre: \( (re^{i\theta})^n = r^ne^{in\theta} \)
Polar: \( z = r(\cos\theta + i\sin\theta) = re^{i\theta} \)
Multiplication: \( r_1e^{i\theta_1} \cdot r_2e^{i\theta_2} = r_1r_2e^{i(\theta_1+\theta_2)} \)
De Moivre: \( (re^{i\theta})^n = r^ne^{in\theta} \)
Euler's Formula
\( e^{i\theta} = \cos\theta + i\sin\theta \)
\( \cos\theta = \frac{e^{i\theta} + e^{-i\theta}}{2} \)
\( \sin\theta = \frac{e^{i\theta} - e^{-i\theta}}{2i} \)
\( \cos\theta = \frac{e^{i\theta} + e^{-i\theta}}{2} \)
\( \sin\theta = \frac{e^{i\theta} - e^{-i\theta}}{2i} \)
Complex Functions
Cauchy-Riemann Equations
\( f(z) = u(x,y) + iv(x,y) \) analytic if:
\( \frac{\partial u}{\partial x} = \frac{\partial v}{\partial y} \), \( \frac{\partial u}{\partial y} = -\frac{\partial v}{\partial x} \)
\( \frac{\partial u}{\partial x} = \frac{\partial v}{\partial y} \), \( \frac{\partial u}{\partial y} = -\frac{\partial v}{\partial x} \)
Complex Integration
Cauchy's Theorem: \( \oint_\gamma f(z)dz = 0 \) if f analytic inside ฮณ
Cauchy's Formula: \( f(a) = \frac{1}{2\pi i} \oint_\gamma \frac{f(z)}{z-a}dz \)
\( f^{(n)}(a) = \frac{n!}{2\pi i} \oint_\gamma \frac{f(z)}{(z-a)^{n+1}}dz \)
Cauchy's Formula: \( f(a) = \frac{1}{2\pi i} \oint_\gamma \frac{f(z)}{z-a}dz \)
\( f^{(n)}(a) = \frac{n!}{2\pi i} \oint_\gamma \frac{f(z)}{(z-a)^{n+1}}dz \)
Residue Theorem
Residue Calculation
Simple pole: \( \text{Res}(f, a) = \lim_{z\to a} (z-a)f(z) \)
Pole order m: \( \text{Res}(f, a) = \frac{1}{(m-1)!} \lim_{z\to a} \frac{d^{m-1}}{dz^{m-1}}[(z-a)^m f(z)] \)
Residue Theorem: \( \oint_\gamma f(z)dz = 2\pi i \sum \text{Res}(f, a_k) \)
Pole order m: \( \text{Res}(f, a) = \frac{1}{(m-1)!} \lim_{z\to a} \frac{d^{m-1}}{dz^{m-1}}[(z-a)^m f(z)] \)
Residue Theorem: \( \oint_\gamma f(z)dz = 2\pi i \sum \text{Res}(f, a_k) \)
Discrete Mathematics Formulas
Combinatorics
Counting Principles
Permutations: \( P(n,r) = \frac{n!}{(n-r)!} \)
Combinations: \( C(n,r) = \binom{n}{r} = \frac{n!}{r!(n-r)!} \)
With repetition: \( \binom{n+r-1}{r} \)
Binomial: \( (x+y)^n = \sum_{k=0}^n \binom{n}{k} x^{n-k}y^k \)
Combinations: \( C(n,r) = \binom{n}{r} = \frac{n!}{r!(n-r)!} \)
With repetition: \( \binom{n+r-1}{r} \)
Binomial: \( (x+y)^n = \sum_{k=0}^n \binom{n}{k} x^{n-k}y^k \)
Inclusion-Exclusion
\( |A \cup B| = |A| + |B| - |A \cap B| \)
\( |A \cup B \cup C| = |A| + |B| + |C| - |A \cap B| - |A \cap C| - |B \cap C| + |A \cap B \cap C| \)
\( |A \cup B \cup C| = |A| + |B| + |C| - |A \cap B| - |A \cap C| - |B \cap C| + |A \cap B \cap C| \)
Graph Theory
Basic Properties
Handshaking: \( \sum_{v \in V} \deg(v) = 2|E| \)
Complete graph \( K_n \): \( \frac{n(n-1)}{2} \) edges
Tree with n vertices: n-1 edges
Planar: \( |V| - |E| + |F| = 2 \) (Euler)
Complete graph \( K_n \): \( \frac{n(n-1)}{2} \) edges
Tree with n vertices: n-1 edges
Planar: \( |V| - |E| + |F| = 2 \) (Euler)
Paths & Cycles
Hamiltonian path: visits each vertex once
Eulerian path: visits each edge once
Dijkstra's algorithm for shortest path
Eulerian path: visits each edge once
Dijkstra's algorithm for shortest path
Logic & Proofs
Logical Equivalences
De Morgan: \( \neg(p \land q) \equiv \neg p \lor \neg q \)
\( \neg(p \lor q) \equiv \neg p \land \neg q \)
Implication: \( p \rightarrow q \equiv \neg p \lor q \)
Contrapositive: \( p \rightarrow q \equiv \neg q \rightarrow \neg p \)
\( \neg(p \lor q) \equiv \neg p \land \neg q \)
Implication: \( p \rightarrow q \equiv \neg p \lor q \)
Contrapositive: \( p \rightarrow q \equiv \neg q \rightarrow \neg p \)
Proof Techniques
Direct proof
Proof by contradiction
Proof by induction: Base case + inductive step
Proof by contrapositive
Proof by contradiction
Proof by induction: Base case + inductive step
Proof by contrapositive
Advanced Calculus Formulas
Vector Calculus
Gradient, Divergence, Curl
Gradient: \( \nabla f = \left\langle \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}, \frac{\partial f}{\partial z} \right\rangle \)
Divergence: \( \nabla \cdot \vec{F} = \frac{\partial F_x}{\partial x} + \frac{\partial F_y}{\partial y} + \frac{\partial F_z}{\partial z} \)
Curl: \( \nabla \times \vec{F} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ \frac{\partial}{\partial x} & \frac{\partial}{\partial y} & \frac{\partial}{\partial z} \\ F_x & F_y & F_z \end{vmatrix} \)
Divergence: \( \nabla \cdot \vec{F} = \frac{\partial F_x}{\partial x} + \frac{\partial F_y}{\partial y} + \frac{\partial F_z}{\partial z} \)
Curl: \( \nabla \times \vec{F} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ \frac{\partial}{\partial x} & \frac{\partial}{\partial y} & \frac{\partial}{\partial z} \\ F_x & F_y & F_z \end{vmatrix} \)
Vector Calculus Theorems
Divergence Theorem: \( \iiint_V (\nabla \cdot \vec{F}) dV = \oiint_S \vec{F} \cdot d\vec{S} \)
Stokes' Theorem: \( \iint_S (\nabla \times \vec{F}) \cdot d\vec{S} = \oint_C \vec{F} \cdot d\vec{r} \)
Green's Theorem: \( \oint_C (P dx + Q dy) = \iint_D \left(\frac{\partial Q}{\partial x} - \frac{\partial P}{\partial y}\right) dA \)
Stokes' Theorem: \( \iint_S (\nabla \times \vec{F}) \cdot d\vec{S} = \oint_C \vec{F} \cdot d\vec{r} \)
Green's Theorem: \( \oint_C (P dx + Q dy) = \iint_D \left(\frac{\partial Q}{\partial x} - \frac{\partial P}{\partial y}\right) dA \)
Fourier Analysis
Fourier Series
\( f(x) = \frac{a_0}{2} + \sum_{n=1}^\infty \left[a_n \cos\left(\frac{2\pi nx}{T}\right) + b_n \sin\left(\frac{2\pi nx}{T}\right)\right] \)
\( a_n = \frac{2}{T} \int_0^T f(x) \cos\left(\frac{2\pi nx}{T}\right) dx \)
\( b_n = \frac{2}{T} \int_0^T f(x) \sin\left(\frac{2\pi nx}{T}\right) dx \)
\( a_n = \frac{2}{T} \int_0^T f(x) \cos\left(\frac{2\pi nx}{T}\right) dx \)
\( b_n = \frac{2}{T} \int_0^T f(x) \sin\left(\frac{2\pi nx}{T}\right) dx \)
Fourier Transform
\( \hat{f}(\xi) = \int_{-\infty}^\infty f(x) e^{-2\pi i x \xi} dx \)
Inverse: \( f(x) = \int_{-\infty}^\infty \hat{f}(\xi) e^{2\pi i x \xi} d\xi \)
Convolution: \( (f * g)(x) = \int_{-\infty}^\infty f(y)g(x-y) dy \)
Inverse: \( f(x) = \int_{-\infty}^\infty \hat{f}(\xi) e^{2\pi i x \xi} d\xi \)
Convolution: \( (f * g)(x) = \int_{-\infty}^\infty f(y)g(x-y) dy \)
Numerical Analysis Formulas
Root Finding Methods
Iterative Methods
Bisection: \( x_{n+1} = \frac{a_n + b_n}{2} \)
Newton-Raphson: \( x_{n+1} = x_n - \frac{f(x_n)}{f'(x_n)} \)
Secant: \( x_{n+1} = x_n - f(x_n)\frac{x_n - x_{n-1}}{f(x_n) - f(x_{n-1})} \)
Newton-Raphson: \( x_{n+1} = x_n - \frac{f(x_n)}{f'(x_n)} \)
Secant: \( x_{n+1} = x_n - f(x_n)\frac{x_n - x_{n-1}}{f(x_n) - f(x_{n-1})} \)
Fixed Point Iteration
\( x_{n+1} = g(x_n) \)
Convergence if \( |g'(x)| < 1 \) near root
Convergence if \( |g'(x)| < 1 \) near root
Numerical Integration
Quadrature Rules
Trapezoidal: \( \int_a^b f(x)dx \approx \frac{b-a}{2}[f(a) + f(b)] \)
Simpson's 1/3: \( \int_a^b f(x)dx \approx \frac{b-a}{6}[f(a) + 4f(\frac{a+b}{2}) + f(b)] \)
Simpson's 3/8: \( \int_a^b f(x)dx \approx \frac{b-a}{8}[f(a) + 3f(\frac{2a+b}{3}) + 3f(\frac{a+2b}{3}) + f(b)] \)
Simpson's 1/3: \( \int_a^b f(x)dx \approx \frac{b-a}{6}[f(a) + 4f(\frac{a+b}{2}) + f(b)] \)
Simpson's 3/8: \( \int_a^b f(x)dx \approx \frac{b-a}{8}[f(a) + 3f(\frac{2a+b}{3}) + 3f(\frac{a+2b}{3}) + f(b)] \)
Composite Rules
Composite Trapezoidal: \( \frac{h}{2}[f(x_0) + 2\sum_{i=1}^{n-1} f(x_i) + f(x_n)] \)
Composite Simpson: \( \frac{h}{3}[f(x_0) + 4\sum_{i=1,3,5}^{n-1} f(x_i) + 2\sum_{i=2,4,6}^{n-2} f(x_i) + f(x_n)] \)
Composite Simpson: \( \frac{h}{3}[f(x_0) + 4\sum_{i=1,3,5}^{n-1} f(x_i) + 2\sum_{i=2,4,6}^{n-2} f(x_i) + f(x_n)] \)
Numerical Differentiation
Finite Differences
Forward: \( f'(x) \approx \frac{f(x+h) - f(x)}{h} \)
Backward: \( f'(x) \approx \frac{f(x) - f(x-h)}{h} \)
Central: \( f'(x) \approx \frac{f(x+h) - f(x-h)}{2h} \)
Backward: \( f'(x) \approx \frac{f(x) - f(x-h)}{h} \)
Central: \( f'(x) \approx \frac{f(x+h) - f(x-h)}{2h} \)
Higher Order Approximations
\( f''(x) \approx \frac{f(x+h) - 2f(x) + f(x-h)}{h^2} \)
\( f^{(4)}(x) \approx \frac{f(x+2h) - 4f(x+h) + 6f(x) - 4f(x-h) + f(x-2h)}{h^4} \)
\( f^{(4)}(x) \approx \frac{f(x+2h) - 4f(x+h) + 6f(x) - 4f(x-h) + f(x-2h)}{h^4} \)
Partial Differential Equations Formulas
Classification & Methods
PDE Classification
Wave: \( u_{tt} = c^2 u_{xx} \) (Hyperbolic)
Heat: \( u_t = \alpha u_{xx} \) (Parabolic)
Laplace: \( u_{xx} + u_{yy} = 0 \) (Elliptic)
General: \( A u_{xx} + B u_{xy} + C u_{yy} + \dots = 0 \)
Heat: \( u_t = \alpha u_{xx} \) (Parabolic)
Laplace: \( u_{xx} + u_{yy} = 0 \) (Elliptic)
General: \( A u_{xx} + B u_{xy} + C u_{yy} + \dots = 0 \)
Separation of Variables
Assume \( u(x,t) = X(x)T(t) \)
Substitute into PDE and separate variables
Solve resulting ODEs with boundary conditions
Substitute into PDE and separate variables
Solve resulting ODEs with boundary conditions
Specific PDE Solutions
Heat Equation Solutions
Fundamental: \( u(x,t) = \frac{1}{\sqrt{4\pi\alpha t}} e^{-x^2/(4\alpha t)} \)
Fourier series solution for bounded domains
Error function solutions for semi-infinite domains
Fourier series solution for bounded domains
Error function solutions for semi-infinite domains
Wave Equation Solutions
d'Alembert: \( u(x,t) = f(x-ct) + g(x+ct) \)
Fourier series for vibrating string
Spherical waves in 3D
Fourier series for vibrating string
Spherical waves in 3D
Abstract Algebra Formulas
Group Theory
Group Properties
Closure: \( a,b \in G \Rightarrow ab \in G \)
Associativity: \( (ab)c = a(bc) \)
Identity: \( \exists e \in G: ea = ae = a \)
Inverse: \( \forall a \in G, \exists a^{-1}: aa^{-1} = a^{-1}a = e \)
Associativity: \( (ab)c = a(bc) \)
Identity: \( \exists e \in G: ea = ae = a \)
Inverse: \( \forall a \in G, \exists a^{-1}: aa^{-1} = a^{-1}a = e \)
Group Theorems
Lagrange: \( |H| \) divides \( |G| \) for subgroup H
Cayley: Every group isomorphic to permutation group
Sylow: Existence of p-subgroups
Cayley: Every group isomorphic to permutation group
Sylow: Existence of p-subgroups
Ring Theory
Ring Properties
Additive group: \( (R,+) \) abelian group
Multiplication: associative, distributive
Commutative ring: multiplication commutative
Field: commutative ring with multiplicative inverses
Multiplication: associative, distributive
Commutative ring: multiplication commutative
Field: commutative ring with multiplicative inverses
Ideal Theory
Ideal: subgroup closed under multiplication by ring elements
Principal ideal: \( (a) = \{ra : r \in R\} \)
Maximal ideal: not contained in any proper ideal
Prime ideal: \( ab \in P \Rightarrow a \in P \) or \( b \in P \)
Principal ideal: \( (a) = \{ra : r \in R\} \)
Maximal ideal: not contained in any proper ideal
Prime ideal: \( ab \in P \Rightarrow a \in P \) or \( b \in P \)
Field Theory
Field Extensions
Degree: \( [F(\alpha):F] = \deg(\text{minimal polynomial}) \)
Finite extension: \( [K:F] < \infty \)
Algebraic extension: every element algebraic over F
Transcendental extension: contains transcendental element
Finite extension: \( [K:F] < \infty \)
Algebraic extension: every element algebraic over F
Transcendental extension: contains transcendental element
Galois Theory
Galois group: \( \text{Gal}(K/F) = \{\sigma: K \to K \mid \sigma|_F = id\} \)
Fundamental theorem: Correspondence between subgroups and intermediate fields
Solvability by radicals related to solvable Galois group
Fundamental theorem: Correspondence between subgroups and intermediate fields
Solvability by radicals related to solvable Galois group
Topology Formulas
Basic Topological Concepts
Topological Space
Collection of open sets satisfying:
1. โ and X are open
2. Union of open sets is open
3. Finite intersection of open sets is open
1. โ and X are open
2. Union of open sets is open
3. Finite intersection of open sets is open
Continuity & Homeomorphism
f continuous if \( f^{-1}(U) \) open for all open U
Homeomorphism: bijective continuous map with continuous inverse
Topological invariant: property preserved by homeomorphism
Homeomorphism: bijective continuous map with continuous inverse
Topological invariant: property preserved by homeomorphism
Separation Axioms
Hausdorff Spaces
T2: โ distinct points x,y, โ disjoint open sets U,V with xโU, yโV
Regular: T1 + points and closed sets separable
Normal: T1 + disjoint closed sets separable
Completely regular: T1 + points and closed sets separated by continuous functions
Regular: T1 + points and closed sets separable
Normal: T1 + disjoint closed sets separable
Completely regular: T1 + points and closed sets separated by continuous functions
Compactness & Connectedness
Compact Spaces
Every open cover has finite subcover
Continuous image of compact is compact
Closed subset of compact is compact
Heine-Borel: In โโฟ, compact = closed and bounded
Continuous image of compact is compact
Closed subset of compact is compact
Heine-Borel: In โโฟ, compact = closed and bounded
Connectedness
Connected: cannot be partitioned into two nonempty disjoint open sets
Path-connected: any two points connected by continuous path
Components: maximal connected subsets
Continuous image of connected is connected
Path-connected: any two points connected by continuous path
Components: maximal connected subsets
Continuous image of connected is connected
Mathematical Physics Formulas
Classical Mechanics
Lagrangian Mechanics
Lagrangian: \( L = T - V \)
Euler-Lagrange: \( \frac{d}{dt}\left(\frac{\partial L}{\partial \dot{q}_i}\right) - \frac{\partial L}{\partial q_i} = 0 \)
Action: \( S = \int_{t_1}^{t_2} L dt \)
Euler-Lagrange: \( \frac{d}{dt}\left(\frac{\partial L}{\partial \dot{q}_i}\right) - \frac{\partial L}{\partial q_i} = 0 \)
Action: \( S = \int_{t_1}^{t_2} L dt \)
Hamiltonian Mechanics
Hamiltonian: \( H = \sum p_i \dot{q}_i - L \)
Hamilton's equations: \( \dot{q}_i = \frac{\partial H}{\partial p_i}, \dot{p}_i = -\frac{\partial H}{\partial q_i} \)
Poisson bracket: \( \{f,g\} = \sum \left(\frac{\partial f}{\partial q_i}\frac{\partial g}{\partial p_i} - \frac{\partial f}{\partial p_i}\frac{\partial g}{\partial q_i}\right) \)
Hamilton's equations: \( \dot{q}_i = \frac{\partial H}{\partial p_i}, \dot{p}_i = -\frac{\partial H}{\partial q_i} \)
Poisson bracket: \( \{f,g\} = \sum \left(\frac{\partial f}{\partial q_i}\frac{\partial g}{\partial p_i} - \frac{\partial f}{\partial p_i}\frac{\partial g}{\partial q_i}\right) \)
Quantum Mechanics
Schrรถdinger Equation
Time-dependent: \( i\hbar\frac{\partial \psi}{\partial t} = \hat{H}\psi \)
Time-independent: \( \hat{H}\psi = E\psi \)
Hamiltonian: \( \hat{H} = -\frac{\hbar^2}{2m}\nabla^2 + V(\vec{r}) \)
Time-independent: \( \hat{H}\psi = E\psi \)
Hamiltonian: \( \hat{H} = -\frac{\hbar^2}{2m}\nabla^2 + V(\vec{r}) \)
Quantum Operators
Position: \( \hat{x}\psi = x\psi \)
Momentum: \( \hat{p} = -i\hbar\frac{\partial}{\partial x} \)
Commutator: \( [\hat{A},\hat{B}] = \hat{A}\hat{B} - \hat{B}\hat{A} \)
Uncertainty: \( \sigma_A \sigma_B \geq \frac{1}{2}|\langle[\hat{A},\hat{B}]\rangle| \)
Momentum: \( \hat{p} = -i\hbar\frac{\partial}{\partial x} \)
Commutator: \( [\hat{A},\hat{B}] = \hat{A}\hat{B} - \hat{B}\hat{A} \)
Uncertainty: \( \sigma_A \sigma_B \geq \frac{1}{2}|\langle[\hat{A},\hat{B}]\rangle| \)
Electromagnetism
Maxwell's Equations
Gauss: \( \nabla \cdot \vec{E} = \frac{\rho}{\epsilon_0} \)
Gauss (mag): \( \nabla \cdot \vec{B} = 0 \)
Faraday: \( \nabla \times \vec{E} = -\frac{\partial \vec{B}}{\partial t} \)
Ampรจre-Maxwell: \( \nabla \times \vec{B} = \mu_0\vec{J} + \mu_0\epsilon_0\frac{\partial \vec{E}}{\partial t} \)
Gauss (mag): \( \nabla \cdot \vec{B} = 0 \)
Faraday: \( \nabla \times \vec{E} = -\frac{\partial \vec{B}}{\partial t} \)
Ampรจre-Maxwell: \( \nabla \times \vec{B} = \mu_0\vec{J} + \mu_0\epsilon_0\frac{\partial \vec{E}}{\partial t} \)
Electromagnetic Waves
Wave equation: \( \nabla^2 \vec{E} = \mu_0\epsilon_0\frac{\partial^2 \vec{E}}{\partial t^2} \)
Speed of light: \( c = \frac{1}{\sqrt{\mu_0\epsilon_0}} \)
Poynting vector: \( \vec{S} = \frac{1}{\mu_0}\vec{E} \times \vec{B} \)
Speed of light: \( c = \frac{1}{\sqrt{\mu_0\epsilon_0}} \)
Poynting vector: \( \vec{S} = \frac{1}{\mu_0}\vec{E} \times \vec{B} \)
Financial Mathematics Formulas
Time Value of Money
Compound Interest
Future value: \( FV = PV(1 + r)^n \)
Present value: \( PV = \frac{FV}{(1 + r)^n} \)
Continuous compounding: \( FV = PVe^{rt} \)
Effective annual rate: \( \left(1 + \frac{r}{m}\right)^m - 1 \)
Present value: \( PV = \frac{FV}{(1 + r)^n} \)
Continuous compounding: \( FV = PVe^{rt} \)
Effective annual rate: \( \left(1 + \frac{r}{m}\right)^m - 1 \)
Annuities
Ordinary annuity: \( PV = PMT\frac{1 - (1+r)^{-n}}{r} \)
Annuity due: \( PV = PMT\frac{1 - (1+r)^{-n}}{r}(1+r) \)
Perpetuity: \( PV = \frac{PMT}{r} \)
Annuity due: \( PV = PMT\frac{1 - (1+r)^{-n}}{r}(1+r) \)
Perpetuity: \( PV = \frac{PMT}{r} \)
Options & Derivatives
Black-Scholes Model
Call option: \( C = S_0N(d_1) - Ke^{-rT}N(d_2) \)
Put option: \( P = Ke^{-rT}N(-d_2) - S_0N(-d_1) \)
\( d_1 = \frac{\ln(S_0/K) + (r + \sigma^2/2)T}{\sigma\sqrt{T}} \)
\( d_2 = d_1 - \sigma\sqrt{T} \)
Put option: \( P = Ke^{-rT}N(-d_2) - S_0N(-d_1) \)
\( d_1 = \frac{\ln(S_0/K) + (r + \sigma^2/2)T}{\sigma\sqrt{T}} \)
\( d_2 = d_1 - \sigma\sqrt{T} \)
Greeks
Delta: \( \Delta = \frac{\partial C}{\partial S} \)
Gamma: \( \Gamma = \frac{\partial^2 C}{\partial S^2} \)
Theta: \( \Theta = \frac{\partial C}{\partial t} \)
Vega: \( \nu = \frac{\partial C}{\partial \sigma} \)
Rho: \( \rho = \frac{\partial C}{\partial r} \)
Gamma: \( \Gamma = \frac{\partial^2 C}{\partial S^2} \)
Theta: \( \Theta = \frac{\partial C}{\partial t} \)
Vega: \( \nu = \frac{\partial C}{\partial \sigma} \)
Rho: \( \rho = \frac{\partial C}{\partial r} \)
Portfolio Theory
Modern Portfolio Theory
Expected return: \( E[R_p] = \sum w_i E[R_i] \)
Portfolio variance: \( \sigma_p^2 = \sum\sum w_i w_j \sigma_{ij} \)
Sharpe ratio: \( \frac{E[R_p] - R_f}{\sigma_p} \)
Capital Market Line: \( E[R] = R_f + \frac{E[R_m] - R_f}{\sigma_m} \sigma \)
Portfolio variance: \( \sigma_p^2 = \sum\sum w_i w_j \sigma_{ij} \)
Sharpe ratio: \( \frac{E[R_p] - R_f}{\sigma_p} \)
Capital Market Line: \( E[R] = R_f + \frac{E[R_m] - R_f}{\sigma_m} \sigma \)
CAPM
\( E[R_i] = R_f + \beta_i(E[R_m] - R_f) \)
\( \beta_i = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)} \)
Security Market Line
\( \beta_i = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)} \)
Security Market Line
Operations Research Formulas
Linear Programming
Standard Form
Maximize \( c^T x \)
Subject to \( Ax \leq b \)
\( x \geq 0 \)
Dual problem: Minimize \( b^T y \) subject to \( A^T y \geq c, y \geq 0 \)
Subject to \( Ax \leq b \)
\( x \geq 0 \)
Dual problem: Minimize \( b^T y \) subject to \( A^T y \geq c, y \geq 0 \)
Simplex Method
Basic feasible solution
Pivot operations
Reduced costs: \( c_j - c_B^T B^{-1} A_j \)
Optimality condition: all reduced costs โค 0
Pivot operations
Reduced costs: \( c_j - c_B^T B^{-1} A_j \)
Optimality condition: all reduced costs โค 0
Queueing Theory
M/M/1 Queue
Arrival rate: ฮป, Service rate: ฮผ
Utilization: \( \rho = \frac{\lambda}{\mu} \)
Average number in system: \( L = \frac{\rho}{1-\rho} \)
Average wait time: \( W = \frac{1}{\mu-\lambda} \)
Utilization: \( \rho = \frac{\lambda}{\mu} \)
Average number in system: \( L = \frac{\rho}{1-\rho} \)
Average wait time: \( W = \frac{1}{\mu-\lambda} \)
Little's Law
\( L = \lambda W \)
\( L_q = \lambda W_q \)
Applies to any stable queueing system
\( L_q = \lambda W_q \)
Applies to any stable queueing system
Network Optimization
Shortest Path
Dijkstra's algorithm
Bellman-Ford algorithm
Floyd-Warshall algorithm
A* search algorithm
Bellman-Ford algorithm
Floyd-Warshall algorithm
A* search algorithm
Maximum Flow
Ford-Fulkerson algorithm
Max-flow min-cut theorem
Residual networks
Augmenting paths
Max-flow min-cut theorem
Residual networks
Augmenting paths
Actuarial Mathematics Formulas
Life Contingencies
Survival Functions
Survival probability: \( _tp_x = \frac{S(x+t)}{S(x)} \)
Force of mortality: \( \mu_x = -\frac{d}{dx}\ln S(x) \)
Life expectancy: \( \overset{\circ}{e}_x = \int_0^\infty {}_tp_x dt \)
Force of mortality: \( \mu_x = -\frac{d}{dx}\ln S(x) \)
Life expectancy: \( \overset{\circ}{e}_x = \int_0^\infty {}_tp_x dt \)
Life Insurance
Whole life: \( A_x = \sum_{k=0}^\infty v^{k+1} {}_kp_x q_{x+k} \)
Term insurance: \( A^1_{x:\angl{n}} = \sum_{k=0}^{n-1} v^{k+1} {}_kp_x q_{x+k} \)
Endowment: \( A_{x:\angl{n}} = A^1_{x:\angl{n}} + v^n {}_np_x \)
Term insurance: \( A^1_{x:\angl{n}} = \sum_{k=0}^{n-1} v^{k+1} {}_kp_x q_{x+k} \)
Endowment: \( A_{x:\angl{n}} = A^1_{x:\angl{n}} + v^n {}_np_x \)
Annuities & Premiums
Life Annuities
Whole life annuity: \( \ddot{a}_x = \sum_{k=0}^\infty v^k {}_kp_x \)
Temporary annuity: \( \ddot{a}_{x:\angl{n}} = \sum_{k=0}^{n-1} v^k {}_kp_x \)
Deferred annuity: \( _{m|\ddot{a}_x} = v^m {}_mp_x \ddot{a}_{x+m} \)
Temporary annuity: \( \ddot{a}_{x:\angl{n}} = \sum_{k=0}^{n-1} v^k {}_kp_x \)
Deferred annuity: \( _{m|\ddot{a}_x} = v^m {}_mp_x \ddot{a}_{x+m} \)
Net Premiums
Equivalence principle: \( E[PV benefits] = E[PV premiums] \)
Whole life: \( P_x = \frac{A_x}{\ddot{a}_x} \)
n-year term: \( P^1_{x:\angl{n}} = \frac{A^1_{x:\angl{n}}}{\ddot{a}_{x:\angl{n}}} \)
Whole life: \( P_x = \frac{A_x}{\ddot{a}_x} \)
n-year term: \( P^1_{x:\angl{n}} = \frac{A^1_{x:\angl{n}}}{\ddot{a}_{x:\angl{n}}} \)
Cryptography Formulas
Public Key Cryptography
RSA Algorithm
Key generation: Choose primes p,q, n = pq, ฯ(n) = (p-1)(q-1)
Public key: (n,e) where gcd(e,ฯ(n)) = 1
Private key: d where ed โก 1 mod ฯ(n)
Encryption: c โก m^e mod n
Decryption: m โก c^d mod n
Public key: (n,e) where gcd(e,ฯ(n)) = 1
Private key: d where ed โก 1 mod ฯ(n)
Encryption: c โก m^e mod n
Decryption: m โก c^d mod n
Diffie-Hellman
Public parameters: prime p, generator g
Alice: A = g^a mod p
Bob: B = g^b mod p
Shared secret: K = B^a mod p = A^b mod p = g^{ab} mod p
Alice: A = g^a mod p
Bob: B = g^b mod p
Shared secret: K = B^a mod p = A^b mod p = g^{ab} mod p
Elliptic Curve Cryptography
Elliptic Curve Operations
Curve: yยฒ = xยณ + ax + b mod p
Point addition: P + Q = R
Point doubling: P + P = 2P
Scalar multiplication: kP = P + P + ... + P (k times)
Point addition: P + Q = R
Point doubling: P + P = 2P
Scalar multiplication: kP = P + P + ... + P (k times)
ECDH & ECDSA
ECDH: Similar to Diffie-Hellman using elliptic curves
ECDSA: Digital signature algorithm using elliptic curves
Smaller key sizes with equivalent security to RSA
ECDSA: Digital signature algorithm using elliptic curves
Smaller key sizes with equivalent security to RSA
Game Theory Formulas
Strategic Games
Nash Equilibrium
Strategy profile where no player can improve payoff by unilaterally changing strategy
Pure strategy Nash equilibrium
Mixed strategy Nash equilibrium
Existence guaranteed by Nash's theorem
Pure strategy Nash equilibrium
Mixed strategy Nash equilibrium
Existence guaranteed by Nash's theorem
Prisoner's Dilemma
Payoff matrix analysis
Dominant strategy equilibrium
Pareto efficiency vs. Nash equilibrium
Iterated prisoner's dilemma
Dominant strategy equilibrium
Pareto efficiency vs. Nash equilibrium
Iterated prisoner's dilemma
Extensive Form Games
Backward Induction
Solve game tree from terminal nodes backward
Subgame perfect equilibrium
Sequential rationality
Perfect information games
Subgame perfect equilibrium
Sequential rationality
Perfect information games
Bayesian Games
Games with incomplete information
Type spaces and beliefs
Bayesian Nash equilibrium
Signaling games
Type spaces and beliefs
Bayesian Nash equilibrium
Signaling games
Information Theory Formulas
Entropy & Information
Shannon Entropy
\( H(X) = -\sum_{i=1}^n p(x_i) \log_2 p(x_i) \)
Joint entropy: \( H(X,Y) = -\sum_{x,y} p(x,y) \log_2 p(x,y) \)
Conditional entropy: \( H(Y|X) = -\sum_{x,y} p(x,y) \log_2 p(y|x) \)
Joint entropy: \( H(X,Y) = -\sum_{x,y} p(x,y) \log_2 p(x,y) \)
Conditional entropy: \( H(Y|X) = -\sum_{x,y} p(x,y) \log_2 p(y|x) \)
Mutual Information
\( I(X;Y) = H(X) - H(X|Y) = H(Y) - H(Y|X) \)
\( I(X;Y) = \sum_{x,y} p(x,y) \log_2 \frac{p(x,y)}{p(x)p(y)} \)
Measures shared information between X and Y
\( I(X;Y) = \sum_{x,y} p(x,y) \log_2 \frac{p(x,y)}{p(x)p(y)} \)
Measures shared information between X and Y
Channel Capacity
Channel Coding Theorem
Channel capacity: \( C = \max_{p(x)} I(X;Y) \)
Shannon's theorem: Rates below C are achievable
Noisy channel coding theorem
Error-correcting codes
Shannon's theorem: Rates below C are achievable
Noisy channel coding theorem
Error-correcting codes
Specific Channels
Binary symmetric channel: \( C = 1 - H(p) \)
Gaussian channel: \( C = \frac{1}{2} \log_2(1 + \text{SNR}) \)
Bandlimited channel: \( C = B \log_2(1 + \frac{S}{N_0B}) \)
Gaussian channel: \( C = \frac{1}{2} \log_2(1 + \text{SNR}) \)
Bandlimited channel: \( C = B \log_2(1 + \frac{S}{N_0B}) \)
Special Functions Formulas
Gamma & Beta Functions
Gamma Function
\( \Gamma(z) = \int_0^\infty t^{z-1} e^{-t} dt \)
\( \Gamma(n+1) = n! \) for integer n
\( \Gamma(z+1) = z\Gamma(z) \)
\( \Gamma(\frac{1}{2}) = \sqrt{\pi} \)
\( \Gamma(n+1) = n! \) for integer n
\( \Gamma(z+1) = z\Gamma(z) \)
\( \Gamma(\frac{1}{2}) = \sqrt{\pi} \)
Beta Function
\( B(x,y) = \int_0^1 t^{x-1}(1-t)^{y-1} dt \)
\( B(x,y) = \frac{\Gamma(x)\Gamma(y)}{\Gamma(x+y)} \)
Symmetry: \( B(x,y) = B(y,x) \)
\( B(x,y) = \frac{\Gamma(x)\Gamma(y)}{\Gamma(x+y)} \)
Symmetry: \( B(x,y) = B(y,x) \)
Bessel Functions
Bessel's Equation
\( x^2 y'' + x y' + (x^2 - \nu^2)y = 0 \)
First kind: \( J_\nu(x) = \sum_{m=0}^\infty \frac{(-1)^m}{m!\Gamma(m+\nu+1)}\left(\frac{x}{2}\right)^{2m+\nu} \)
Second kind: \( Y_\nu(x) \) (Neumann function)
First kind: \( J_\nu(x) = \sum_{m=0}^\infty \frac{(-1)^m}{m!\Gamma(m+\nu+1)}\left(\frac{x}{2}\right)^{2m+\nu} \)
Second kind: \( Y_\nu(x) \) (Neumann function)
Properties & Relations
Recurrence: \( J_{\nu-1}(x) + J_{\nu+1}(x) = \frac{2\nu}{x} J_\nu(x) \)
Derivatives: \( \frac{d}{dx}[x^\nu J_\nu(x)] = x^\nu J_{\nu-1}(x) \)
Orthogonality: \( \int_0^1 x J_\nu(\alpha x) J_\nu(\beta x) dx = 0 \) for ฮฑโ ฮฒ
Derivatives: \( \frac{d}{dx}[x^\nu J_\nu(x)] = x^\nu J_{\nu-1}(x) \)
Orthogonality: \( \int_0^1 x J_\nu(\alpha x) J_\nu(\beta x) dx = 0 \) for ฮฑโ ฮฒ
Legendre & Hermite Polynomials
Legendre Polynomials
Rodrigues: \( P_n(x) = \frac{1}{2^n n!} \frac{d^n}{dx^n}[(x^2-1)^n] \)
Generating: \( \frac{1}{\sqrt{1-2xt+t^2}} = \sum_{n=0}^\infty P_n(x) t^n \)
Orthogonality: \( \int_{-1}^1 P_m(x) P_n(x) dx = \frac{2}{2n+1} \delta_{mn} \)
Generating: \( \frac{1}{\sqrt{1-2xt+t^2}} = \sum_{n=0}^\infty P_n(x) t^n \)
Orthogonality: \( \int_{-1}^1 P_m(x) P_n(x) dx = \frac{2}{2n+1} \delta_{mn} \)
Hermite Polynomials
Rodrigues: \( H_n(x) = (-1)^n e^{x^2} \frac{d^n}{dx^n} e^{-x^2} \)
Generating: \( e^{2xt-t^2} = \sum_{n=0}^\infty H_n(x) \frac{t^n}{n!} \)
Orthogonality: \( \int_{-\infty}^\infty H_m(x) H_n(x) e^{-x^2} dx = \sqrt{\pi} 2^n n! \delta_{mn} \)
Generating: \( e^{2xt-t^2} = \sum_{n=0}^\infty H_n(x) \frac{t^n}{n!} \)
Orthogonality: \( \int_{-\infty}^\infty H_m(x) H_n(x) e^{-x^2} dx = \sqrt{\pi} 2^n n! \delta_{mn} \)