Probability: Difference between revisions
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* Indicator random variable | * Indicator random variable | ||
* Expectation | * Expectation | ||
* Decomposition principle | * Decomposition principle - relevant for the analysis of randomized algorithms. | ||
* Linearity of expectations | * Linearity of expectations | ||
* Conditional probability | * Conditional probability | ||
Revision as of 00:29, 21 September 2021
Internal
Overview
TODO
- 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
Discrete Probability
Concepts:
- Sample space
- Propabilites
- 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