Foundations of Statistics for Economic Analysis

Are you looking to understand the quantitative side of economic policy and research? Statistical methods are the backbone of modern economic analysis. This course provides a robust, practical introduction to statistical inference and modeling tailored specifically for economic applications. You will move beyond theoretical concepts to confidently apply foundational statistical techniques necessary for interpreting real-world economic data. What you'll learn: Understand core probability theory, descriptive statistics, and sampling distributions essential for inference. Master the principles of hypothesis testing and statistical estimation using real economic examples. Apply simple and multiple linear regression models to analyze relationships between economic variables. Practice interpreting regression outputs, assessing model fit, and recognizing common pitfalls like omitted variable bias. Learn fundamental concepts of causal inference and the essential requirements for establishing correlation versus causation in data. The curriculum begins with foundational concepts in probability and statistical distributions, progressing systematically through estimation, hypothesis testing, and culminating in practical applications of regression analysis. You will work through structured exercises designed to solidify your understanding of statistical reasoning. This course is designed for absolute beginners in statistics, especially students and professionals in economics, finance, and social sciences. Familiarity with basic algebra is helpful, but no prior statistical knowledge is required. Start building your quantitative analysis skills today.