Introduction to Probability and Statistics with Theory

A first course in calculus-based probability and statistics. Topics include data fluency, probability spaces, discrete and continuous random variables, expected values, law of large numbers, central limit theorem, point estimation, confidence intervals, hypothesis testing, measures of association, linear regression, and example applications. This course introduces students to the mathematical theory and formalism needed for upper-level undergraduate courses in probability and statistics. Prerequisites: Multivariable calculus; Linear algebra.