Fundamentals of Applied Probability

Basic equation

V a r ( x ) = E [ ( x − E ( x ) ) 2 ] = E ( x 2 ) − E 2 ( x ) \mathrm{Var}(x)=E[(x-E(x))^2]=E(x^2)-E^2(x) V a r ( x )=And [ ( xE ( x ) )2]=And ( x2)E2(x)

E (x + y) = E (x) + E (y) E (x + y) = E (x) + E (y) And ( x+and )=E ( x )+E ( and )

if x x x and y y y are independent, then:

E (xy) = E (x) + E (y) E (xy) = E (x) + E (y) E(xy)=E ( x )+E ( and )

V a r ( x + y ) = V a r ( x ) + V a r ( y ) \mathrm{Var}(x+y)=\mathrm{Var}(x)+\mathrm{Var}(y) V a r ( x+and )=V a r ( x )+V a r ( y )

if x 1 , ⋯   , x n x_1,\cdots,x_n x1,,xn are pairwise independent, then:

V a r ( x 1 + ⋯ + x n ) = V a r ( x 1 ) + ⋯ + V a r ( x n ) \mathrm{Var}(x_1+\cdots+x_n) = \mathrm{Var}(x_1)+\cdots+\mathrm{Var}(x_n) V a r ( x1++xn)=V a r ( x1)++V a r ( xn)

Basic inequality

( 1 + x ) a ≤ e a x , x ∈ R (1+x)^a\le e^{ax},\quad x \in \mathbb R (1+x)aeax,xR

( 1 + x ) a ≥ 1 + a x , a ∈ [ 1 , + ∞ ) ,   x ∈ ( − 1 , + ∞ ) (1+x)^a \ge 1+ax, \quad a \in [1,+\infty),\ x\in (-1,+\infty) (1+x)a1+ax,a[1,+), x(1,+) (Bernoulli)

ln ⁡ ( 1 + x ) ≤ x , x ∈ ( − 1 , + ∞ ) \ln(1+x)\le x, \quad x\in (-1, +\infty) ln(1+x)x,x(1,+)

ln ⁡ ( 1 + x ) ≥ x − x 2 , x ∈ ( − 1 2 , + ∞ ) \ln(1+x)\ge x-x^2, \quad x\in (-\dfrac12,+\infty) ln(1+x)xx2,x(21,+)

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