Probability and Statistics for Civil and Environmental Engineering

Engineering decisions are always made under conditions of uncertainty, whether you are designing resilient infrastructure or analyzing environmental systems. This text-based course bridges the gap between theoretical probability and practical engineering applications, giving you the tools to model and analyze risk with confidence. You will transition from basic probability concepts to modeling complex systems with multiple random variables. By completing this course, you will be able to analyze engineering data, model joint uncertainties, and evaluate the reliability of structural and environmental systems. You will learn to apply discrete and continuous random vectors to real-world scenarios, ensuring your engineering designs are safe, sustainable, and mathematically sound. What you'll learn: - Understand foundational probability concepts and statistical terminology used in engineering - Model multiple sources of uncertainty using discrete and continuous random vectors - Analyze independent random variables to simplify complex engineering risk calculations - Apply joint probability distributions to structural safety and environmental impact assessments - Calculate marginal and conditional distributions to make data-driven engineering decisions This course begins with essential definitions and core mathematical foundations before guiding you through joint distributions, covariance, and independence. You will read through clear explanations, step-by-step derivations, and practical engineering case studies that reinforce each concept. This course is designed for engineering students and practicing professionals who want a solid foundation in probability and statistics. No prior background in advanced statistics is required, though a basic understanding of calculus is helpful. Start reading today to build safer, more resilient engineering systems using modern statistical methods.