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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:

  1. 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.
  2. Understand basic statistical estimation procedures, including maximum likelihood estimation and method of moments.
  3. Understand the concept of hypothesis testing and be able to apply appropriate statistical tests for comparing means, proportions and variances.
  4. Understand the concept of interval estimation and be able to find the confidence intervals of means, proportions and variances.
  5. Understand the law of large numbers and the central limit theorem and how they are applied in the development of statistical theory.