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Introductory Business Statistics

Formula Review

Introductory Business StatisticsFormula Review

5.1 Properties of Continuous Probability Density 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 )

  • 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

  • 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
  • Additionally
    • P(X > x) = e(–mx)
    • P(a < X < b) = e(–ma)e(–mb)
  • Poisson probability: P(X=x)= μ x e μ x! P(X=x)= μ x e μ x! with mean and variance of μ
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