Second introductory course covering basic principles of probability and statistical inference. Topics: Point estimation, interval estimating, and testing hypotheses, Bayesian approaches to inference.
Introductory course covering basic principles of probability and statistical inference. Topics covered in this course: Axiomatic definition of probability, random variables, probability distributions, expectation.
This sequence is ideal for students or early data science professionals who want to strengthen their knowledge of fundamental probability and statistics concepts. Mastery of Mathematical Fundamentals is a prerequisite.