Probability & Statistics: Core Concepts and Distributions

Many fields, from data science to engineering, rely on a strong grasp of probability and statistics. This course provides the essential building blocks for quantitative reasoning. By the end of this course, you will possess a robust theoretical foundation in probability and statistics, enabling you to interpret data, understand statistical inference, and confidently tackle more advanced topics. What you'll learn: Understand fundamental probability axioms, sample spaces, and events. Apply conditional probability and Bayes' Theorem to update beliefs based on new information. Explore key discrete and continuous probability distributions and their moments. Grasp the concepts of expectation, variance, and characteristic functions. Learn the Central Limit Theorem and its critical role in statistical inference. Analyze different modes of convergence for sequences of random variables. Interpret the foundational concepts that underpin modern data analysis and statistical modeling. This course systematically introduces core probability theory, progresses through various distributions and their properties, and culminates in essential limit theorems crucial for statistical understanding. This course is designed for absolute beginners with no prior knowledge of probability or statistics, as well as those seeking to reinforce their foundational understanding. Begin your journey into the world of quantitative reasoning today.