example 11.31 A length measurement

Rests on

• depends_on definition 11.8 Quantiles and median ¶
  • depends_on definition 11.3 Discrete random variable ¶
    • depends_on definition 11.1 Discrete probability space ¶
      • depends_on definition 7.45 Series ¶
        • depends_on definition 7.2 Absolute value ¶
        • depends_on definition 7.4 Convergence ¶
• depends_on definition 11.16 Sample mean, variance and correlation ¶
  • depends_on definition 11.11 Covariance and correlation ¶
    • depends_on definition 11.6 Moments, variance, standard deviation ¶
      • depends_on proposition 11.5 Transfer, linearity, monotonicity ¶
        • depends_on definition 11.4 Expectation ¶
        • depends_on proposition 11.2 Elementary rules ¶
        • proves proof ch:09-probability-statistics@proof-2 ¶
    • depends_on proposition 11.5 Transfer, linearity, monotonicity ¶ ↺
  • depends_on definition 11.13 Independence ¶
    • depends_on definition 11.3 Discrete random variable ¶ ↺
  • depends_on definition 11.6 Moments, variance, standard deviation ¶ ↺
• depends_on proposition 11.17 Sampling identities ¶
  • depends_on definition 11.16 Sample mean, variance and correlation ¶ ↺
  • depends_on proposition 11.12 Bilinearity ¶
    • depends_on definition 11.11 Covariance and correlation ¶ ↺
    • depends_on proposition 11.5 Transfer, linearity, monotonicity ¶ ↺
    • proves proof ch:09-probability-statistics@proof-5 ¶
  • depends_on proposition 11.14 Independence implies zero covariance; the converse fails ¶
    • depends_on definition 11.13 Independence ¶ ↺
    • depends_on proposition 11.12 Bilinearity ¶ ↺
    • proves proof ch:09-probability-statistics@proof-6 ¶
  • proves proof ch:09-probability-statistics@proof-8 ¶

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