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5.1 Continuous Probability Functions

Probability density function (pdf) f(x):

  • f(x) ≥ 0
  • The total area under the curve f(x) is one.

Cumulative distribution function (cdf): P(Xx)

5.2 The Uniform Distribution

X = a real number between a and b (in some instances, X can take on the values a and b). a = smallest X; b = largest X

X ~ U (a, b)

The mean is μ= a+b 2 μ= a+b 2

The standard deviation is σ= (b – a) 2 12 σ= (b – a) 2 12

Probability density function: f(x)= 1 ba f(x)= 1 ba for aXb aXb

Area to the Left of x: P(X < x) = (xa) ( 1 ba ) ( 1 ba )

Area to the Right of x: P(X > x) = (bx) ( 1 ba ) ( 1 ba )

Area Between c and d: P(c < x < d) = (base)(height) = (dc) ( 1 ba ) ( 1 ba )

Uniform: X ~ U(a, b) where a < x < b

  • pdf: f( x )= 1 ba f( x )= 1 ba for a ≤ x ≤ b
  • cdf: P(Xx) = xa ba xa ba
  • mean µ = a+b 2 a+b 2
  • standard deviation σ = (ba) 2 12 = (ba) 2 12
  • P(c < X < d) = (dc) ( 1 ba ) ( 1 ba )

5.3 The Exponential Distribution

Exponential: X ~ Exp(m) where m = the decay parameter

  • pdf: f(x) = me(–mx) where x ≥ 0 and m > 0
  • cdf: P(Xx) = 1 – e(–mx)
  • mean µ = 1 m 1 m
  • standard deviation σ = µ
  • percentile k: k = ln(1AreaToTheLeftOfk) (m) ln(1AreaToTheLeftOfk) (m)
  • Additionally
    • P(X > x) = e(–mx)
    • P(a < X < b) = e(–ma)e(–mb)
  • Memoryless Property: P(X > x + k|X > x) = P (X > k)
  • Poisson probability:  P(X=k)= λ k e k k!  P(X=k)= λ k e k k! with mean λ
  • k! = k*(k-1)*(k-2)*(k-3)*…3*2*1
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