Introduction to Statistics and Probability

5 credits

Overview of probability; conditional probability and independence; Bayes Theorem; discrete and continuous random variables including jointly distributed; key distributions including the normal and its spin offs; properties of expectation and variance; conditional expectation; covariance and correlation; Central Limit Theorem; law of large numbers; Parameter Estimation. Offered: jointly with BIOST 556/DATA 556; A.