Introduction to Probability for Statistics

Catalog description

Introduction to probability to provide foundation for inferential statistics. Topics include axioms of probability, independence, conditional probability, Bayes theorem, random variables, common discrete and continuous probability distributions, bivariate and multivariate distributions, marginal and conditional distributions, expectations, distributions of functions of random variables, covariance and correlation. Equal emphasis is placed on analytical and simulation-based methods for understanding probability. Students will learn to implement these computational methods using R statistical software. Approaches to assessing the accuracy of simulation methods are discussed. Prereq: MATH 122 or MATH 124 or MATH 126 .