Statistics
Deepen your knowledge of applied statistics and improve your command of statistical theory and applications with these classes.
Course information and details will be updated as they become available. Visit the department listings to see more info.
Introduction to Statistics (without calculus)
Designed for students in fields that emphasize quantitative methods. Graphical and numerical summaries, probability, theory of sampling distributions, linear regression, confidence intervals, and hypothesis testing are taught as aids to quantitative reasoning and data analysis. Use of statistical software required. Illustrations are taken from a variety of fields. Data-collection/analysis project with emphasis on study designs is part of the coursework requirement.
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Introduction to Statistics (with calculus)
Designed for students who desire a strong grounding in statistical concepts with a greater degree of mathematical rigor. Topics covered include: random variables, probability distributions, pdf, cdf, mean, variance, correlation, conditional distribution, conditional mean and conditional variance, law of iterated expectations, normal, chi-square, F and t distributions, law of large numbers, central limit theorem, parameter estimation, unbiasedness, consistency, efficiency, hypothesis testing, p-value, confidence intervals and maximum likelihood estimation.
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Probability
This course can be taken as a single course for students requiring knowledge of probability or as a foundation for more advanced courses. Topics covered include combinatorics, conditional probability, random variables and common distributions, expectation, independence, Bayes' rule, joint distributions, conditional expectations, moment generating functions, central limit theorem, laws of large numbers, characteristic functions.
see department listings