This book offers a comprehensive guide to using GNU Octave for data analysis, econometrics, and statistical modeling. Beginning with an introduction to Octave's history, setup, and key differences from MATLAB, readers quickly move into practical skills, learning basic commands, data handling, and scripting. Core statistical concepts such as descriptive analysis, regression, and time series methods are explained clearly with real-world examples. Advanced topics including Maximum Likelihood Estimation, Cointegration, Vector Autoregression, Panel Data Econometrics, Monte Carlo Simulations, GMM, and ARCH/GARCH models are also thoroughly covered. Each chapter blends theory with hands-on Octave implementation, making complex techniques accessible and applicable. Whether you're a student, researcher, or professional, this book equips you with the tools to confidently analyze and model data in Octave. No prior experience with Octave is assumed, making it ideal for beginners and those transitioning from other platforms.