Description
I. Randomness.- 2. Probability.- 3. Independent Events.- 4. Conditional Probability.- 5. Bayes’ Theorem.- 6. Review of Randomness. Part II Discrete Random Variables 7. Discrete Versus Continuous Random Variables.- 8.- Probability Mass Functions and CDFs.- 9. Independence and Conditioning.- 10. Expected Values of Discrete Random Variables.- 11. Expected Values of Sums of Random Variables.- 12. Variance of Discrete Random Variables.- 13. Review of Discrete Random Variables. Part III Named Discrete Random Variables 14.- Bernoulli Random Variables.- 15. Binomial Random Variables.- 16. Geometric Random Variables.- 17.Negative Binomial Random Variables.- 18. Poisson Random Variables.- 19. Hypergeometric Random Variables.- 20. Discrete Uniform Random Variables.- 21. Review of Named Discrete Random Variables. Part IV Counting 22. Introduction to Counting.- 23. Two Case Studies in Counting. Part V Continuous Random Variables 24. Continuous Random Variables and PDFs.- 25. Joint Densities.- 26. Independent Continuous Random Variables.- 27. Conditional Distributions.- 28. Expected Values of Continuous Random Variables.- 29. Variance of Continuous Random Variables.- 30. Review of Continuous Random Variables Part VI Named Continuous Random Variables 31. Continuous Uniform Random Variables.- 32. Exponential Random Variables.- 33. Gamma Random Variables.- 34. Beta Random Variables.- 35. Normal Random Variables.- 36. Sums of Independent Normal Random Variables.- 37. Central Limit Theorem Part VII Additional Topics 39. Variance of Sums; Covariance; Correlation.- 40. Conditional Expectation.- 41. Markov and Chebyshev Inequalities.- 42. Order Statistics.- 43. Moment Generating Functions.- 44.
