Probability and Inference 1

University of Otago

Course Description

  • Course Name

    Probability and Inference 1

  • Host University

    University of Otago

  • Location

    Dunedin, New Zealand

  • Area of Study

    Mathematics, Statistics

  • Language Level

    Taught In English

  • Prerequisites

    MATH 160 and one of STAT 110, STAT 115, COMO 101, BSNS 102, BSNS 112, QUAN 101

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Credit Points

  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4 - 6
  • Overview

    An introduction to probability theory and mathematical statistics. Probability, random variables, sampling distributions, estimation, hypothesis testing, simulation.

    In the first year, Statistics papers emphasise the methods of statistics: which techniques and tests are applied in which situations. In this paper, you will learn some of the theory and mathematics behind those methods. This is important because you will:

    • Better understand where those standard methods come from and why they are used
    • Learn how to conduct analyses and design statistical methods for the many cases in which the 'standard' toolbox is inadequate

    Modern statistics is a dynamic and rapidly changing subject. If you are going to keep up with the changes and advances in statistical theory and methodology, you will need a good grounding in mathematical statistics and probability theory.

    Course Structure
    Main topics:

    • Introduction to probability
    • Random variables and distributions
    • Expectation and variance
    • Transformations of random variables
    • Statistical models
    • Estimators and likelihood
    • Confidence intervals and hypothesis testing
    • Bayesian inference

    Learning Outcomes
    Students who successfully complete the paper will develop an ability to conduct analyses and design statistical methods for cases in which the 'standard' toolbox is inadequate

Course Disclaimer

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