Math 2.0

Resources / course

Introduction to Probability Theory and Statistics 2S7T7E5Y87

URIm2://res/2S7T7E5Y87
Kindcourse
CreatorsS Dharmaraja (instructor)
Date2022-07-05
Scopein
Idscourse 049tgcd06:111102160

Expressions

e1: edition

Languageen
Date2022-07-05
Contents
  • part 1: week-01
  • session 1: Lecture 1
  • session 2: Random experiment, sample space, axioms of probability, probability space. (Cont...)
  • session 3: Random experiment, sample space, axioms of probability, probability space. (Contd...)
  • session 4: Conditional probability, independence of events.
  • session 5: Multiplication rule, total probability rule, Bayes's theorem.
  • part 2: week-02
  • session 6: Lecture 6
  • session 7: Definition of Random Variable, Cumulative Distribution Function (Continued 1)
  • session 8: Definition of Random Variable, Cumulative Distribution Function (Continued 2)
  • session 9: Type of Random Variables, Probability Mass Function, Probability Density Function
  • session 10: Type of Random Variables, Probability Mass Function, Probability Density Function (continued 1)
  • session 11: Distribution of Function of Random Variables
  • part 3: week-03
  • session 12: Lecture 12
  • session 13: Mean and Variance Continued
  • session 14: Higher Order Moments and Moments Inequalities
  • session 15: Higher Order Moments and Moments Inequalities Continued
  • session 16: Generating Functions
  • session 17: Generating Functions Continued
  • part 4: week-04
  • session 18: Lecture 18
  • session 19: Common Discrete Distributions Continued
  • session 20: Common Continuous Distributions
  • session 21: Common Continuous Distributions Continued
  • session 22: Applications of Random Variable
  • session 23: Applications of Random Variable Continued
  • part 5: week-05
  • session 24: Lecture 24
  • session 25: Joint probability mass function
  • session 26: Joint probability density function
  • session 27: Independent random variables
  • session 28: Independent random variables Continued
  • part 6: week-06
  • session 29: Lecture 29
  • session 30: Functions of several random variables continued
  • session 31: Some important results
  • session 32: Order statistics
  • session 33: Conditional distributions
  • session 34: Random sum
  • part 7: week-07
  • session 35: Lecture 35
  • session 36: Variance Covariance matrix
  • session 37: Multivariate Normal distribution
  • session 38: Probability generating function and Moment generating function
  • session 39: Correlation coefficient
  • session 40: Conditional Expectation
  • session 41: Conditional Expectation continued.
  • part 8: week-08
  • session 42: Lecture 42
  • session 43: Mode of Convergence (Continued)
  • session 44: Law of Large Numbers
  • session 45: Central Limit Theorem
  • session 46: Central Limit Theorem (Continued)
  • part 9: week-09
  • session 47: Lecture 47
  • session 48: Lecture 48
  • session 49: Lecture 49
  • part 10: week-10
  • session 50: Lecture 50
  • session 51: Lecture 51
  • session 52: Lecture 52
  • part 11: week-11
  • session 53: Lecture 53
  • session 54: Lecture 54
  • session 55: Lecture 55
  • part 12: week-12
  • session 56: Lecture 56
  • session 57: Lecture 57
  • session 58: Lecture 58

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