Probability: Difference between revisions
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* Mathematics for Computer Science Eric Lehman and Tom Leighton Chapters 18 - Chapter 25. | |||
* https://www.coursera.org/learn/algorithms-divide-conquer/lecture/UXerT/probability-review-i | * https://www.coursera.org/learn/algorithms-divide-conquer/lecture/UXerT/probability-review-i | ||
* https://www.coursera.org/learn/algorithms-divide-conquer/lecture/cPGDy/probability-review-ii | * https://www.coursera.org/learn/algorithms-divide-conquer/lecture/cPGDy/probability-review-ii | ||
Map Concepts: | |||
Concepts: | |||
* Sample space | * Sample space | ||
* Outcome | * Outcome | ||
Revision as of 21:56, 22 September 2021
Internal
Overview
All concepts discussed in this page are discrete probability concepts.
Sample Space and Probability Space
Notations
TODO
- Mathematics for Computer Science Eric Lehman and Tom Leighton Chapters 18 - Chapter 25.
- https://www.coursera.org/learn/algorithms-divide-conquer/lecture/UXerT/probability-review-i
- https://www.coursera.org/learn/algorithms-divide-conquer/lecture/cPGDy/probability-review-ii
Map Concepts:
- Sample space
- Outcome
- Probabilites
- Events and outocomes
- Random variables
- Indicator random variable
- Expectation
- Decomposition principle - relevant for the analysis of randomized algorithms.
- Linearity of expectations
- Conditional probability
- Independent events
- Independent random variables
- Probability distribution