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Georgetown University


Detailed Course Information


Fall 2017
Jan 16, 2018
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Information Select the desired Level or Schedule Type to find available classes for the course.

BIST 510 - Probability & Sampling
The goal of the course is to convey an understanding of probability and distribution theory. The probability theory is necessary to provide a foundation for statistics. Probability theory: set theory and probability theory, conditional probability and independence, random variables, distribution functions, density and mass functions for continuous and discrete random variables. Transformation and expectations: distributions of functions of a random variable, expected values, moments and moment generating functions. Common families of distributions: discrete and continuous distributions, exponential family, and location-scale family. Multiple random variables: joint and marginal distributions, conditional distributions and independence, covariance and correlation, multivariate distributions, hierarchical models and mixture distributions. Sampling theory: normal theory, limit theorems.

3.000 Credit hours
3.000 Lecture hours
0.000 Lab hours

Levels: MN or MC Graduate, Undergraduate
Schedule Types: Lecture

Biostatistics & Epidemiology Department

Must be enrolled in one of the following Levels:     
      MN or MC Graduate
Must be enrolled in one of the following Majors:     
      Mathematics and Statistics

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