Probability Theory: Understanding Joint, Marginal, & Conditional Probability

Math    |    Intermediate
  • 13 videos | 1h 36m 17s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 4 users Rating 5.0 of 4 users (4)
Probability is all about estimating the likeliness of the occurrence of specific events. Use this course to learn more about defining and measuring joint, marginal, and conditional probabilities of events. Start by exploring the chain rule of probability and then use this rule to compute conditional probabilities of multiple events. You'll also investigate the steps involved in measuring the expected value of a random variable as the weighted sum of all outcomes, with each outcome weighted by its probability. By the time you finish this course, you will be able to compute joint, marginal, and conditional probabilities and the expected value of a random variable, as well as effectively utilize the chain rule of probability.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Define joint, marginal, and conditional probability
    Link the definitions of marginal and conditional probability
    Outline the chain rule of probability
    Calculate joint probabilities associated with the rolling of a die
    Compute marginal probabilities
    Compute conditional probabilities
  • Simulate the rolling of two die to test joint probability
    Calculate the joint probability of dependent variables
    Calculate marginal and conditional probability on dependent variables
    Define the formula of the expected value of a random variable
    Compute the expected value of the rolling of a die
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 40s
  • 8m 3s
  • Locked
    3.  Components of Marginal and Conditional Probability
    8m 6s
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    4.  Chained Rule and Joint Probability of Events
    8m 38s
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    5.  Calculating Marginal Probabilities
    7m 29s
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    6.  Applying the Chain Rule to Conditional Probabilities
    10m 33s
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    7.  Computing Joint Probabilities on Dice Rolls
    6m 35s
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    8.  Exploring Joint Probability with Dependent Variables
    10m 24s
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    9.  Computing Marginal and Conditional Probabilities with Dependent Variables
    7m 23s
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    10.  Defining the Expected Value of a Random Variable
    11m 23s
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    11.  Computing Expected Value of a Random Variable
    7m 33s
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    12.  Computing Expected Value of a Dice Roll
    6m 54s
  • Locked
    13.  Course Summary
    1m 38s

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