expected value

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1. 1▶Engineering Probability Lecture 15: Joint expectations; correlation and covarianceEngineering ProbabilityNotes
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2. 2▶Engineering Probability Lecture 14: Two random variables (continuous); independenceEngineering ProbabilityNotes
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3. 3▶Engineering Probability Lecture 13: Two random variables (discrete)Engineering ProbabilityNotes
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4. 4▶Engineering Probability Lecture 12: Functions of a random variable; inequalitiesEngineering ProbabilityNotes
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5. 5▶Engineering Probability Lecture 11: Expected value for continuous random variablesEngineering ProbabilityNotes
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6. 6▶Engineering Probability Lecture 10: The Gaussian random variable and Q functionEngineering ProbabilityNotes
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7. 7▶Engineering Probability Lecture 9: Probability density functions and continuous random variablesEngineering ProbabilityNotes
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8. 8▶Engineering Probability Lecture 8: Cumulative distribution functions (CDFs)Engineering ProbabilityNotes
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9. 9▶Engineering Probability Lecture 7: Conditional probability mass functionsEngineering ProbabilityNotes
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10. 10▶Engineering Probability Lecture 6: Expected value and momentsEngineering ProbabilityNotes
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11. 11▶4.1 Standard error of a random sumSTAT 2.2x: Probability | UC BerkeleyNotes
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12. 12▶2.3 Sampling without replacement: hypergeometric distributionSTAT 2.2x: Probability | UC BerkeleyNotes
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13. 13▶2.2 Sampling with replacement: binomial distributionSTAT 2.2x: Probability | UC BerkeleyNotes
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14. 14▶3.1 Not the law of averagesSTAT 2.2x: Probability | UC BerkeleyNotes
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15. 15▶3.4 Expected value of a sample averageSTAT 2.2x: Probability | UC BerkeleyNotes
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16. 16▶3.3 Expected value of a sample sumSTAT 2.2x: Probability | UC BerkeleyNotes
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17. 17▶2.4 ExamplesSTAT 2.2x: Probability | UC BerkeleyNotes
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18. 18▶3.2 The law of averagesSTAT 2.2x: Probability | UC BerkeleyNotes
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19. 19▶1.4 Problem solving techniquesSTAT 2.2x: Probability | UC BerkeleyNotes
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20. 20▶1.6 Bayes' RuleSTAT 2.2x: Probability | UC BerkeleyNotes
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