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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 11: Derived Distributions (M-I-T) » L11.4 A Linear Function of a Normal Random Variable (M-I-T)

L11.4 A Linear Function of a Normal Random Variable (M-I-T)

Course:Lecture 11: Derived Distributions (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:Graduate

Lecture 11: Derived Distributions (M-I-T)

L11.1 Lecture Overview (M-I-T)
L11.2 The PMF of a Function of a Discrete Random Variable (M-I-T)
L11.3 A Linear Function of a Continuous Random Variable (M-I-T)
L11.4 A Linear Function of a Normal Random Variable (M-I-T)
L11.5 The PDF of a General Function (M-I-T)
L11.6 The Monotonic Case (M-I-T)
L11.7 The Intuition for the Monotonic Case (M-I-T)
L11.8 A Nonmonotonic Example (M-I-T)
L11.9 The PDF of a Function of Multiple Random Variables (M-I-T)
S11.1 Simulation (M-I-T)

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