Probability Bites

Probability Bites

Rich Radke via YouTube Direct link

PB55: Conditional Expectation Practice Problems

56 of 75

56 of 75

PB55: Conditional Expectation Practice Problems

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Probability Bites

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  1. 1 PB 0: Introduction
  2. 2 PB 1: Experiments and Sample Spaces
  3. 3 PB 2: Events
  4. 4 PB 3: Axioms of Probability
  5. 5 PB 4: Discrete Sample Spaces
  6. 6 PB 5: Combinatorics
  7. 7 PB 6: Combinatorics Practice Problems
  8. 8 PB 7: Continuous Sample Spaces
  9. 9 PB 8: Conditional Probability
  10. 10 PB 9: The Total Probability Theorem
  11. 11 PB 10: Bayes' Rule
  12. 12 PB11: A Medical Testing Example
  13. 13 PB12: The Monty Hall Problem
  14. 14 PB13: Independent Events
  15. 15 PB14: Bernoulli Trials
  16. 16 PB15: Binomial and Geometric Practice Problems
  17. 17 PB16: Bernoulli's Theorem
  18. 18 PB17: Discrete Random Variables
  19. 19 PB18: Probability Mass Function
  20. 20 PB19: The Poisson Random Variable
  21. 21 PB20: Expected Value for Discrete Random Variables
  22. 22 PB21: Expected Value of Functions
  23. 23 PB22: The Variance
  24. 24 PB23: Conditional Probability Mass Functions
  25. 25 PB24: The Memoryless Property
  26. 26 PB25: Conditional Expected Value
  27. 27 PB26: Cumulative Distribution Functions
  28. 28 PB27: Continuous Random Variables
  29. 29 PB28: Probability Density Functions
  30. 30 PB29: The Exponential Random Variable
  31. 31 PB30: The Gaussian Random Variable
  32. 32 PB31: Q Function Practice Problems
  33. 33 PB32: Expected Value for Continuous Random Variables
  34. 34 PB33: Expected Value of Functions of a Random Variable
  35. 35 PB34: Expected Value Practice Problems (Using Integration)
  36. 36 PB35: Expected Value Practice Problems (Using Properties)
  37. 37 PB36: Designing a Quantizer
  38. 38 PB37: One-to-One Functions of a Random Variable
  39. 39 PB38: Many-to-One Functions of a Random Variable
  40. 40 PB39: Markov and Chebyshev Inequalities
  41. 41 PB40: Two Discrete Random Variables
  42. 42 PB41: Joint PMF/CDF for Discrete Random Variables
  43. 43 PB42: The Marginal PMF for Discrete Random Variables
  44. 44 PB43: Joint PDF/CDF and Marginals for Continuous Random Variables
  45. 45 PB44: Joint Random Variable Practice Problems
  46. 46 PB45: The Joint Gaussian Random Variable
  47. 47 PB46: Independence of Random Variables
  48. 48 PB47: Joint Expectations and Covariance
  49. 49 PB48: The Correlation Coefficient
  50. 50 PB49: Conditional PMFs for Discrete Random Variables
  51. 51 PB50: Class-Conditional Probability Density Functions
  52. 52 PB51: The Bayes Decision Rule
  53. 53 PB52: Conditional PDFs for Continuous Joint Random Variables
  54. 54 PB53: Conditional Gaussian Distributions
  55. 55 PB54: The Law of Iterated Expectation
  56. 56 PB55: Conditional Expectation Practice Problems
  57. 57 PB56: More Conditional Expectation Practice Problems
  58. 58 PB57: Sums of Random Variables
  59. 59 PB58: Laws of Large Numbers
  60. 60 PB59: The PDF of a Sum of Random Variables
  61. 61 PB60: Transformations of Random Variables
  62. 62 PB61: The Central Limit Theorem
  63. 63 PB62: Central Limit Theorem Practice Problems
  64. 64 PB63: Weak Law of Large Numbers vs. Central Limit Theorem
  65. 65 PB64: Confidence Intervals
  66. 66 PB65: Maximum A Posteriori (MAP) Estimation
  67. 67 PB66: Maximum Likelihood Estimation
  68. 68 PB67: Minimum Mean-Square Estimation
  69. 69 PB68: Linear Minimum Mean-Square Estimation
  70. 70 PB69: Significance Testing
  71. 71 PB70: Hypothesis Testing
  72. 72 PB71: A Hypothesis Testing Example
  73. 73 PB72: Testing the Fit of a Distribution
  74. 74 PB73: Generating Samples of a Random Variable
  75. 75 PB74: Tips and Tricks for Random Number Generation

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