Statistics for Economists: Foundational Data Analysis

Economic decisions and policies rely heavily on data, but interpreting that data requires a solid grasp of statistical principles. This course introduces you to the core statistical methods used by economists to analyze markets, evaluate policy impact, and understand financial trends. You will transition from reading raw numbers to extracting meaningful, data-driven economic insights. Through clear, step-by-step written explanations and practical examples, you will learn how to summarize economic data, compute probabilities, and perform hypothesis testing to draw reliable conclusions. You will also get introduced to modern data interpretation practices used in today's financial and policy research. What you'll learn: - Understand foundational concepts of descriptive statistics, including mean, variance, and standard deviation in economic contexts. - Learn probability theory and probability distributions to model economic uncertainty and risk. - Apply sampling methods and the Central Limit Theorem to make inferences about large populations. - Formulate and test statistical hypotheses to evaluate economic policies and market claims. - Explore linear regression analysis to identify and analyze relationships between key economic variables. - Practice interpreting statistical outputs and modern data visualizations with confidence. The course begins with key terminology and basic concepts of descriptive statistics before guiding you through probability theory, hypothesis testing, and foundational regression models. Designed for beginners in economics, business, or social sciences, this course requires no prior statistical background. Start reading today to build your analytical foundation in economic statistics.