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Home » Applied Sciences » Engineering » Electrical Engineering and Computer Science (M-I-T) » Introduction to Probability (Spring 2018) (M-I-T) » Part I: The Fundamentals (M-I-T) » Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T) » L12.4 The Sum of Independent Normal Random Variables (M-I-T)

L12.4 The Sum of Independent Normal Random Variables (M-I-T)

Course:Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:Graduate

Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)

L12.10 Interpreting the Correlation Coefficient (M-I-T)
L12.11 Correlations Matter (M-I-T)
L12.1 Lecture Overview (M-I-T)
L12.2 The Sum of Independent Discrete Random Variables (M-I-T)
L12.3 The Sum of Independent Continuous Random Variables (M-I-T)
L12.4 The Sum of Independent Normal Random Variables (M-I-T)
L12.5 Covariance (M-I-T)
L12.6 Covariance Properties (M-I-T)
L12.7 The Variance of the Sum of Random Variables (M-I-T)
L12.8 The Correlation Coefficient (M-I-T)
L12.9 Proof of Key Properties of the Correlation Coefficient (M-I-T)

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