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Course: STAT 23400
Title: Statistical Models and Method 1
Instructor(s): Subhajit Goswami
Course Assistant(s): Nathan Vos
Class Schedule: Sec 03: TR 12:00-1:20PM
Office Hours:  
Textbook(s): Pruim, Foundations and Applications of Statistics
Description: This course is recommended for students throughout the natural and social sciences who want a broad background in statistical methodology and exposure to probability models and the statistical concepts underlying the methodology. Probability is developed for the purpose of modeling outcomes of random phenomena. Random variables and their expectations are studied; including means and variances of linear combinations and an introduction to conditional expectation. Binomial, Poisson, normal and other standard probability distributions are considered. Some probability models are studied mathematically, and others are studied via simulation on a computer. Sampling distributions and related statistical methods are explored mathematically, studied via simulation, and illustrated on data. Methods include, but are not limited to, inference for means and variances for one- and two-sample problems, correlation, and simple linear regression. Graphical description and numerical data description are used for exploration, communication of results, and comparing mathematical consequences of probability models and data. Mathematics employed is to the level of univariate calculus, but it is less demanding than that required by STAT 24400.