This unit introduces continuous random variables and develops their properties in a manner that parallels the development for the discrete case. In addition, it covers a few more advanced topics such as the derivation of the distribution of a function of a random variable, covariance and correlation, and a more abstract view of the conditional expectation.

Lecture 11: Derived Distributions; Convolution; Covariance and Correlation |

Lecture 12: Iterated Expectations; Sum of a Random Number of Random Variables |

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