Foundational Statistics and Econometrics for Economic Analysis

To truly understand complex economic phenomena, analysts must move beyond pure theory and adopt rigorous quantitative methods. This course builds a robust foundation in statistics, mathematical economics, and econometrics, enabling you to understand, build, and critique real-world economic models using data. What you'll learn: * Understand core statistical concepts including probability, distributions, and foundational statistical inference. * Master Ordinary Least Squares (OLS) regression, its underlying assumptions, and the interpretation of regression coefficients. * Apply hypothesis testing techniques to evaluate causal relationships and test economic theories using real-world data. * Analyze and interpret common econometric problems such as multicollinearity, heteroskedasticity, and autocorrelation. * Practice reading and interpreting output generated by standard statistical software packages for model evaluation and reporting. * Configure basic time series models and introduce concepts relevant to macroeconomic forecasting and analysis. The course begins by establishing the necessary mathematical prerequisites and statistical inference principles before moving into simple and multiple linear regression. We then cover essential diagnostic tests required to ensure reliable model results. This content is delivered entirely through clear written explanations and practical application exercises. This course is designed for absolute beginners in quantitative economics. No prior knowledge of advanced statistics or econometrics is required, only basic algebra. Start building your essential toolkit for evidence-based economic research today.