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  • 6.5: Chapter 6 Formulas
    https://stats.libretexts.org/Workbench/Introduction_to_Statistical_Methods_(Yuba_College)/06%3A_Discrete_Probability_Distributions/6.05%3A_Chapter_6_Formulas
    Discrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: P(X = x) = n C x ·p x ·q (n-x ) , x = 0, 1, 2, … ...Discrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: P(X = x) = n C x ·p x ·q (n-x ) , x = 0, 1, 2, … , n Hypergeometric Distribution: P(X = x) = aCx⋅bCn−xNCn Unit Change for Poisson Distribution: New μ = old μ( new units  old units ) Poisson Distribution: P(X = x) = e−μμxx!
  • 4.6: Discrete Probability Formulas
    https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/04%3A_Discrete_Probability_Distributions/4.06%3A_Discrete_Probability_Formulas
    Discrete Distribution Mean: μ = Σ(x i ∙ P(x i )) Discrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: ...Discrete Distribution Mean: μ = Σ(x i ∙ P(x i )) Discrete Distribution Variance: σ 2 = ∑(x i 2 ∙P(x i )) – μ 2 Geometric Distribution: P(X = x) = p ∙ q (x – 1) , x = 1, 2, 3, … Binomial Distribution: P(X = x) = n C x ·p x ·q (n-x ) , x = 0, 1, 2, … , n Hypergeometric Distribution: P(X = x) = aCx⋅bCn−xNCn Poisson Distribution: P(X = x) = e−μμxx!

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