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Page 1: Linear Algebra Formulas - Calvin Collegescofield/courses/m232/materials/fullFormulaSheet.pdfLinear Algebra Formulas ... Normal equations for Ax = b: (ATA)x = ATb Statistics Formulas

Linear Algebra FormulasAngle θ between vectors u, v satisfies: cosθ = 〈u,v〉

|u||v|

Normal equations for Ax = b: (ATA)x = ATb

Statistics FormulasMeans and Variances

Mean Variance

Sample (of size n) x =1n

∑i

xi s2 =1

n − 1

∑i

(xi − x)2

Random variable Xdiscrete X

General E(X) =∑

x x fX(x) Var(X) =∑

x(x − µX)2 fX(x)= E([X − E(X)]2)= E(X2) − [E(X)]2

X ∼ Binom(n, π) E(X) = nπ Var(X) = nπ(1 − π)

X ∼ Hyper(m,n, k) E(X) =km

m + nVar(X) = k

( mm + n

) ( nm + n

) (m + n − km + n − 1

)continuous X

General E(X) =∫∞

−∞x fX(x) dx Var(X) =

∫∞

−∞[x − E(X)]2 fX(x) dx

= E([X − E(X)]2)= E(X2) − [E(X)]2

X ∼ Unif(a, b) E(X) =12

(a + b) Var(X) =1

12(b − a)2

X ∼ Exp(λ) E(X) = 1/λ Var(X) = 1/λ2

X ∼ Norm(µ, σ) E(X) = µ Var(X) = σ2

100(1 − α)% Confidence Intervals

For T ∼ t(ν) choose tβ,ν so that P(T > tβ,ν) = β. The 2-sided 100(1 − α)% CI is

(estimate) ± t∗(std. error) ,

with t∗ = tα/2,ν, and the degrees of freedom ν chosen appropriately (see below).

What estimating? Sample size Estimate std. error ν

µX n xs√

nn − 1

µX − µY m, n (resp.) x − y( sX

m+

sY

n

)1/2

s2X

m+

s2Y

n

2

(s2X/m)2

m − 1+

(s2Y/n)2

n − 1

β1 n b1 sb1 =

√MSE∑

i(xi − x)2 n − 2

Page 2: Linear Algebra Formulas - Calvin Collegescofield/courses/m232/materials/fullFormulaSheet.pdfLinear Algebra Formulas ... Normal equations for Ax = b: (ATA)x = ATb Statistics Formulas

Vector Calculus FormulasFundamental theorems (main result)

FT of Line Integrals: If F = ∇ f , and the curve C has endpoints A and B, then∫C

F · dr = f (B) − f (A).

Green’s Theorem:"

R

(∂N∂x−∂M∂y

)dA =

,C

F · dr (circulation-curl form)

Stokes’ Theorem:"

S∇ × F ·n dσ =

,C

F · dr, where C is the edge curve of S

Green’s Theorem:"

R∇ ·F dA =

,C

F ·n ds (flux-divergence form)

Divergence Theorem:$

R∇ ·F dV =

S

F ·n dσ

Differential elements

Along a parametrized curve r(t), t ∈ [a, b], we have ds =∥∥∥ dr

dt

∥∥∥ dt.Along a parametrized surface r(u, v), (u, v) ∈ D, we have dσ =

∥∥∥ ∂r∂u ×

∂r∂v

∥∥∥ du dv.

Curl and divergence

For a continuously differentiable 3D vector field F(x, y, z) = M(x, y, z)i + N(x, y, z)j + P(x, y, z)k,

curl F = ∇ × F :=(∂P∂y−∂N∂z

)i +

(∂M∂z−∂P∂x

)j +

(∂N∂x−∂M∂y

)k .

div F = ∇ ·F :=(∂∂x,∂∂y,∂∂z

)· (M,N,P) =

∂M∂x

+∂N∂y

+∂P∂z

.

Other 3D spatial coordinates

r =√

x2 + y2 = ρ sinφ,

ρ =√

x2 + y2 + z2,

x = r cosθ = ρ sinφ cosθ,

y = r sinθ = ρ sinφ sinθ,

z = ρ cosφ ,

dV = dz dy dx

= r dz dr dθ

= ρ2 sinφ dρ dφ dθ .