Sign-in Links
STAT 269 Statistics and Probability II Units: 3.00
Basic techniques of statistical estimation such as best unbiased estimates, moment estimates, maximum likelihood. Bayesian methods. Hypotheses testing. Classical distributions such as the t-distribution, F-distribution, beta distribution. These methods will be illustrated by simple linear regression. Statistical computing.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Requirements: Prerequisite (MATH 221 or MATH 280) and (STAT 252 or STAT 268 or STAT 351) or permission of the Department.
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Be able to find the distribution of functions of random variables, and understand how classical distributions such as t-distribution, F-distribution and χ2 distribution are defined.
- Understand basic statistical estimation procedures, including maximum likelihood estimation and method of moments.
- Understand the concept of hypothesis testing and be able to apply appropriate statistical tests for comparing means, proportions and variances.
- Understand the concept of interval estimation and be able to find the confidence intervals of means, proportions and variances.
- Understand the law of large numbers and the central limit theorem and how they are applied in the development of statistical theory.