Introduction to Probability and Statistics 131A. Lecture 9. Conditional Probability

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UCI Math 131A: Introduction to Probability and Statistics (Summer 2013)
Lec 09. Introduction to Probability and Statistics: Conditional Probability
Instructor: Michael C. Cranston, Ph.D.

License: Creative Commons CC-BY-SA

Description: UCI Math 131A is an introductory course covering basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.

Recorded on July 12, 2013

  1. UCI Open
  2. UCI
  3. University of California Irvine
  4. OCW
  5. OpenCourseWare
  6. Math
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Комментарии
Автор

Professor Cranston, thank you for another solid analysis on the Moment Generating Function and its powerful relationship to the Expected Values in Probability and Statistics. By differentiating the Moment Generating Function of X yields the Variance of X. The introduction to Covariance is another well known and important topic in Probability and Statistics. Problem solving is the best way to master these important concepts from start to finish. This is an error free video/lecture on YouTube TV with Professor Michael C. Cranston.

georgesadler
Автор

42:00 looks like they are made for each other

saubaral
Автор

y do your video names make no sense :(

saubaral