# Introduction to Probability and Statistics A - UCI

Description: UCI Math 131A is an introductory course covering basic principles of probability and statistical inference. Axiomatic definition of probability, random variables, probability distributions, expectation.

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Required attribution: Cranston, Michael C. Math 131A (UCI OpenCourseWare: University of California, Irvine), ocw.uci.edu/courses/math_131a_in....html. [Access date]. License: Creative Commons Attribution-ShareAlike 3.0 United States License. (creativecommons.org/licenses/by-...n_US)

## Lessons hide description |
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## 1) Lecture 1. Probability## Lec 01. Introduction to Probability and Statistics: Probability Instructor: Michael C. Cranston, Ph.D. Recorded on June 24, 2013 |

## 2) Lecture 2. Probability## Lec 02. Introduction to Probability and Statistics: Probability Instructor: Michael C. Cranston, Ph.D. Recorded on June 26, 2013 |

## 3) Lecture 3. Random Variables## Lec 03. Introduction to Probability and Statistics: Random Variables Instructor: Michael C. Cranston, Ph.D. Recorded on June 28, 2013 |

## 4) Lecture 4. Joint Distribution## Lec 04. Introduction to Probability and Statistics: Joint Distribution Instructor: Michael C. Cranston, Ph.D. Recorded on July 1, 2013 |

## 5) Lecture 5. Expected Values## Lec 05. Introduction to Probability and Statistics: Expected Values Instructor: Michael C. Cranston, Ph.D. Recorded on July 3, 2013 |

## 6) Lecture 6. Joint Distribution## Lec 06. Introduction to Probability and Statistics: Joint Distribution Instructor: Michael C. Cranston, Ph.D. Recorded on July 5, 2013 |

## 7) Lecture 7. Limit Theorems## Lec 07. Introduction to Probability and Statistics: Limit Theorems Instructor: Michael C. Cranston, Ph.D. Recorded on July 8, 2013 |

## 8) Lecture 8: Distributions from normal Distribution## Lec 08. Introduction to Probability and Statistics: Distributions from normal Distribution Instructor: Michael C. Cranston, Ph.D. Recorded on July 10, 2013 |

## 9) Lecture 9. Conditional Probability## Lec 09. Introduction to Probability and Statistics: Conditional Probability Instructor: Michael C. Cranston, Ph.D. Recorded on July 12, 2013 |

## 10) Lecture 10. Survey Sampling## Lec 10. Introduction to Probability and Statistics: Survey Sampling Instructor: Michael C. Cranston, Ph.D. Recorded on July 15, 2013 |

## 11) Lecture 11. Estimation of Parameters## Lec 11. Introduction to Probability and Statistics: Estimation of Parameters Instructor: Michael C. Cranston, Ph.D. Recorded on July 17, 2013 |

## 12) Lecture 12. Fitting of Probability Distributions## Lec 12. Introduction to Probability and Statistics: Fitting of Probability Distributions Instructor: Michael C. Cranston, Ph.D. Recorded on July 19, 2013 |

## 13) Lecture 13. Hypothesis Testing## Lec 13. Introduction to Probability and Statistics: Hypothesis Testing Instructor: Michael C. Cranston, Ph.D. Recorded on July 22, 2013 |

## 14) Lecture 14. Random Sampling## Lec 14. Introduction to Probability and Statistics: Random Sampling Instructor: Michael C. Cranston, Ph.D. Recorded on July 25, 2013 |

## 15) Lecture 15. Simple Random Sampling## Lec 15. Introduction to Probability and Statistics: Simple Random Sampling Instructor: Michael C. Cranston, Ph.D. Recorded on July 26, 2013 |

## 16) Lecture 16. Final Review## Lec 16. Introduction to Probability and Statistics: Lecture 16. Final Review Instructor: Michael C. Cranston, Ph.D. Recorded on July 29, 2013 |

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