An introduction to the theory of probability, with emphasis on the construction of discrete probability models for applications. First Year Seminars See the First Year Seminar Courses Booklet. Does not count toward any STA programs. Statistical Concepts A survey of statistical methodology with emphasis on data analysis and applications. The topics covered include descriptive statistics, basic probability, simulation, data collection and the design of experiments, tests of significance and confidence intervals, power, multiple regression and the analysis of variance, and count data.
Students learn to use a statistical computer package as part of the course.
Topics include discrete and continuous probability distributions, conditional probability, expectation, sampling distributions, estimation and testing, the linear model. This course is concerned with the development of the probability model. Topics include probability measures, distribution functions, probability and density functions, random variables, conditional probability, expectation, convergence in distribution, the Weak and Strong Laws of Large Numbers, the Central Limit Theorem, some Normal distribution theory and applications. This course presents the theory and methods for the statistical analysis of a broad class of statistical models. Linear models are presented as the subset of those most commonly used.