Foundational Statistics for Economic Analysis

Modern economics and social science rely heavily on quantitative evidence. Developing a strong statistical foundation is the essential first step toward understanding and interpreting complex data models. This course provides a comprehensive introduction to the statistical concepts necessary for conducting economic analysis. You will move from basic probability theory to applying estimation techniques and rigorously testing hypotheses, building the conceptual bedrock needed for advanced econometrics. What you'll learn: * Understand the fundamentals of probability, random variables, and common theoretical distributions. * Apply sampling theory to draw valid inferences about populations from observed economic data. * Master techniques for statistical estimation, including calculating point estimates and confidence intervals. * Practice rigorous hypothesis testing methods (p-values and significance levels) crucial for research. * Analyze correlation and simple linear regression as the basis for understanding relationships between economic variables. * Learn to identify common data biases and potential limitations in statistical modeling and interpretation. The course begins by establishing key terminology and the rules of probability, then progresses through descriptive statistics and sampling techniques before diving into the core methods of inference, estimation, and rigorous hypothesis testing. This course is designed for absolute beginners interested in economics, finance, or social science who need a strong quantitative foundation. No prior statistics knowledge or advanced mathematics is required. Start building your essential quantitative toolkit today.