probability-continuous.rst
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   210 
   210 
   211    E[norm(μ, σ²)] = μ
   211    E[norm(μ, σ²)] = μ
   212 
   212 
   213    var[norm(μ, σ²)] = σ²
   213    var[norm(μ, σ²)] = σ²
   214 
   214 
   215 Disjoint distribution of two normal r.v.
   215 Summa of two normal r.v.
   216 ========================================
   216 ========================
   217 
   217 
   218 .. math::
   218 If :math:`Z = X + Y` and X and Y is independent normal r.v. then:
   219 
   219 
   220    norm2(μ₁, μ₂, σ₁², σ₂²) = norm(μ₁, σ₁²)·norm(μ₂, σ₂²)
   220 .. math:: norm(μ_z, σ_z²) = norm(μ_x+μ_y, σ_x²+σ_y²)
   221 
   221 
   222    = 1/(2·π·σ₁·σ₂)·exp(-(x-μ₁)²/σ₁²/2 - (x-μ₂)²/σ₂²/2)
   222 Proof:
       
   223 
       
   224 .. math::
       
   225 
       
   226    norm(μ_z, σ_z²) = ∫_x\ f_X(x)·f_Y(z-x)\ dx
       
   227 
       
   228    = ∫_x\ 1/sqrt(2·π)/σ_x·exp(-(x-μ_x)²/σ_x²/2)·1/sqrt(2·π)/σ_y·exp(-(z-x-μ_y)²/σ_y²/2)\ dx
       
   229 
       
   230    = 1/sqrt(2·π·(σ_x² + σ_y²))·exp(-(x-μ_x-μ_y)²/(σ_x²+σ_y²)/2)
   223 
   231 
   224 Linear function of distribution
   232 Linear function of distribution
   225 ===============================
   233 ===============================
   226 
   234 
   227 If :math:`Y = a·X + b` then :math:`f_Y(y) = 1/|a|·f_X((y-b)/a)`.
   235 If :math:`Y = a·X + b` then :math:`f_Y(y) = 1/|a|·f_X((y-b)/a)`.
   285 
   293 
   286 and so:
   294 and so:
   287 
   295 
   288 .. math:: f_Y(y) = (d\ f_Y(t)/dt)(y) = (d\ F_X(h(t))/dt)(y) = F_X(h(y))·(d\ h(t)/dt)(y)
   296 .. math:: f_Y(y) = (d\ f_Y(t)/dt)(y) = (d\ F_X(h(t))/dt)(y) = F_X(h(y))·(d\ h(t)/dt)(y)
   289 
   297 
       
   298 Convolution formula
       
   299 ===================
       
   300 
       
   301 If :math:`Z = X + Y` and X and Y is independent r.v. then:
       
   302 
       
   303 .. math:: f_Z(z) = ∫_x\ f_X(x)·f_Y(z-x)̣·dx
       
   304 
       
   305 Proof:
       
   306 
       
   307 Consider :math:`Z` at conditional event :math:`X=x`:
       
   308 
       
   309 .. math:: f_{Z|X}(z|X=x) = f_{z|X=x}(z|X=x)
       
   310 
       
   311 Becasue of independence of :math:`X` and :math:`Y`:
       
   312 
       
   313 .. math:: f_{Z|X}(z|X=x) = f_{X+Y|X=x}(z|X=x) = f_{x+Y}(z) = f_Y(z-x)
       
   314 
       
   315 Joint PDF of :math:`X` and :math:`Z` is:
       
   316 
       
   317 .. math:: f_{X,Z}(x,z) = f_X(x)·f_{Z|X}(z|X=x) = f_X(x)·f_Y(z-x)
       
   318 
       
   319 By integrating by :math:`x` we get:
       
   320 
       
   321 .. math:: f_Z(z) = ∫_x\ f_{X,Z}(x,z)\ dx = ∫_x\ f_X(x)·f_Y(z-x)\ dx
       
   322