Probability Theory: Understanding Joint, Marginal, & Conditional Probability
Math
| Intermediate
- 13 Videos | 1h 36m 17s
- Includes Assessment
- Earns a Badge
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
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discover the key concepts covered in this coursedefine joint, marginal, and conditional probabilitylink the definitions of marginal and conditional probabilityoutline the chain rule of probabilitycalculate joint probabilities associated with the rolling of a diecompute marginal probabilitiescompute conditional probabilities
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simulate the rolling of two die to test joint probabilitycalculate the joint probability of dependent variablescalculate marginal and conditional probability on dependent variablesdefine the formula of the expected value of a random variablecompute the expected value of the rolling of a diesummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 40sUP NEXT
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2.Joint, Marginal, and Conditional Probability8m 3s
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3.Components of Marginal and Conditional Probability8m 6s
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4.Chained Rule and Joint Probability of Events8m 38s
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5.Calculating Marginal Probabilities7m 29s
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6.Applying the Chain Rule to Conditional Probabilities10m 33s
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7.Computing Joint Probabilities on Dice Rolls6m 35s
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8.Exploring Joint Probability with Dependent Variables10m 24s
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9.Computing Marginal and Conditional Probabilities with Dependent Variables7m 23s
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10.Defining the Expected Value of a Random Variable11m 23s
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11.Computing Expected Value of a Random Variable7m 33s
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12.Computing Expected Value of a Dice Roll6m 54s
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13.Course Summary1m 38s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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